We're building the infrastructure that lets people talk to Claude,real-time, bidirectional voice conversations that feel natural, responsive, and safe. This is foundational work for how millions of people will interact with AI.

The Voice Platform team designs and operates the serving systems, streaming pipelines, and APIs that bring Anthropic's audio models from research into production across Claude.ai, our mobile apps, and the Anthropic API. You'll work at the intersection of real-time media, low-latency inference, and distributed systems,building infrastructure where every millisecond of latency is felt by the user.

We partner closely with the Audio research team, who train the speech understanding and generation models, and with product teams shipping voice experiences to users. Your job is to make those models fast, reliable, and delightful to talk to at scale.

Responsibilities

• Design and build the real-time streaming infrastructure that powers voice conversations with Claude,ingesting microphone audio, orchestrating model inference, and streaming synthesized speech back with minimal latency

• Build low-latency serving systems for speech models, optimizing time-to-first-audio and end-to-end conversational responsiveness

• Develop the public and internal APIs that expose voice capabilities to Claude.ai, mobile clients, and third-party developers

• Own the audio transport layer,codecs, jitter buffers, adaptive bitrate, packet loss recovery,so conversations stay smooth across unreliable networks

• Build observability and quality-measurement systems for voice: latency distributions, audio quality metrics, interruption handling, and turn-taking accuracy

• Partner with Audio research to move new model architectures from experiment to production, and feed real-world performance data back into research

• Collaborate with mobile and product engineering on client-side audio capture, playback, and the end-to-end user experience

You may be a good fit if you

• Have 6+ years of experience building distributed systems, real-time infrastructure, or platform services at scale

• Have shipped production systems where latency is measured in tens of milliseconds and users notice when you miss

• Are comfortable working across the stack,from transport protocols and serving infrastructure up to the APIs product teams build on

• Are results-oriented, with a bias toward flexibility and impact

• Pick up slack, even if it goes outside your job description

• Enjoy pair programming (we love to pair!)

• Care about the societal impacts of voice AI and want to help shape how these systems are developed responsibly

• Are comfortable with ambiguity,voice is a fast-moving space, and you'll help define the architecture as we learn what works

Strong candidates may also have experience with

• Real-time media protocols and stacks: WebRTC, RTP, gRPC bidirectional streaming, or WebSockets at scale

• Audio engineering fundamentals: codecs (Opus, AAC), voice activity detection, echo cancellation, jitter buffering, or audio DSP

• Low-latency ML inference serving, streaming model outputs, or GPU-based serving infrastructure

• Telephony, live streaming, video conferencing, or voice assistant platforms

• Mobile audio pipelines on iOS (AVAudioEngine, AudioUnits) or Android (Oboe, AAudio)

• Working alongside ML researchers to productionize models,speech experience is a plus but not required

Representative projects

• Driving time-to-first-audio below human perceptual thresholds by co-designing the serving pipeline with the Audio research team

• Building a streaming inference orchestrator that interleaves speech recognition, LLM reasoning, and speech synthesis with overlapping execution

• Designing the voice mode API surface for the Anthropic API so developers can build their own voice agents on Claude

• Implementing graceful barge-in and interruption handling so users can cut Claude off mid-sentence naturally

• Instrumenting end-to-end audio quality metrics and building dashboards that catch regressions before users do

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This role is critical to securing the infrastructure that powers Anthropic's frontier AI systems across Europe , you'll bridge commercial negotiations with complex internal coordination across legal, finance, engineering, and network teams, and partner closely with our Compute Markets team who own the Europe market strategy and government relationships.

Responsibilities:

• Lead the RFP and commercial sourcing process for European data center deals, managing developer outreach, proposal evaluation, and competitive selection across multiple markets
• Negotiate term sheets and manage the LOI process, structuring commercial terms that meet Anthropic's technical and business requirements while maintaining strong developer partnerships
• Create the bridge from LOI to executed transaction, ensuring all commercial, technical, and legal requirements are satisfied for deal closure
• Serve as project manager for cross-functional stakeholder engagement , coordinating due diligence teams, internal and external legal counsel, network organization, platform engineers, and finance to ensure alignment prior to lease execution
• Act as the single point of contact for auxiliary organizations including networks, deployments, and government relations, providing regular updates on transaction progress and leasing status
• Develop and maintain transaction timelines, tracking critical-path items and proactively identifying risks that could impact deal closure
• Ensure all stakeholder requirements are captured and addressed in commercial agreements, translating technical and operational needs into contractual terms
• Manage complex digital infrastructure development activities to a construction-ready state, through a developer or directly
• Marry the right projects, capital stacks, and developers at the right stages
• Navigate country-specific permitting, grid connection, and regulatory requirements that vary significantly across European markets
• Document and refine transaction processes and playbooks to enable scalable deal execution as Anthropic expands its infrastructure footprint across the region
• Partner with the Compute Markets Manager to prioritize markets, sites, and counterparties, and feed deal learnings back into Europe market strategy

You may be a good fit if you:

• Have 10+ years of experience in transaction management, commercial real estate, data center leasing, or infrastructure procurement
• Possess a proven track record of managing complex, multi-stakeholder transactions from sourcing through execution
• Have strong negotiation skills with experience structuring term sheets, LOIs, and commercial agreements
• Excel at project management and can coordinate across legal, technical, finance, and operational teams simultaneously
• Have experience with RFP processes and competitive sourcing for large-scale infrastructure or real estate transactions
• Have experience working in or across European markets, with knowledge of the regional data center and development landscape , including established FLAP-D hubs and emerging markets like the Nordics and Southern Europe
• Are comfortable operating across multiple countries with different legal frameworks, languages, and business cultures
• Are highly organized with strong attention to detail while maintaining focus on strategic deal objectives
• Can operate effectively in fast-paced, ambiguous environments where processes are being built alongside execution
• Demonstrate exceptional communication skills and can coordinate effectively across time zones with US-based HQ teams and distributed European partners

It's a bonus if you:

• Have experience with data center or hyperscale infrastructure transactions specifically
• Come from the development side of the industry rather than traditional brokerage/leasing , you understand how DC development works and how value is created (yield-on-cost, cap rates, development fees)
• Understand technical requirements for AI/ML workloads including power density, cooling, and network connectivity
• Have worked with legal teams on complex lease negotiations or infrastructure agreements across multiple European jurisdictions
• Understand utility coordination, power procurement, or energy considerations in data center transactions, particularly in the European context (fragmented national power markets, grid connection queues, renewable PPAs, sustainability and efficiency regulations)
• Have familiarity with data sovereignty and regulatory considerations that influence European site selection
• Have relationships within the European data center developer, operator, and broker ecosystem
• Have a background in corporate development, strategic partnerships, or infrastructure investment
• Have experience in high-growth technology companies managing infrastructure expansion

Annual compensation range for this role is £225,000-£270,000 GBP.

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You will work across the full agent lifecycle,from model and system design to evaluation, deployment, and iteration,bridging cutting-edge agentic techniques with the constraints and requirements of real customer environments.

Key responsibilities include:

• Design and implement end-to-end agent systems that combine LLM reasoning, tool use, memory, and control logic to solve recurring enterprise use cases.
• Build scalable, reliable agent architectures that can be deployed across many customers with varying data, tools, and constraints.
• Develop evaluation frameworks, datasets, environments, and metrics to measure agent performance, reliability, and business impact in production settings.
• Collaborate closely with product managers, customers, data annotators, and other engineering teams to translate enterprise requirements into robust agent designs.
• Productionize frontier agent techniques (e.g., planning, multi-step reasoning and tool-use, multi-agent patterns) into maintainable, observable systems.
• Own deployment, monitoring, and iteration of agent systems, including failure analysis and continuous improvement based on real-world usage.
• Contribute to technical direction and architectural decisions for general agent development best practices and methods, with increasing scope and leadership at the Staff level.

Ideal candidates will have:

• 5+ years of experience building and deploying machine learning or AI systems for real-world, production use cases.
• Strong engineering fundamentals, supported by a Bachelor’s and/or Master’s degree in Computer Science, Machine Learning, AI, or equivalent practical experience.
• Deep understanding of modern LLMs, prompt-, context-, and system-level optimization, and agentic system design.
• Proven proficiency in Python, including writing production-quality, testable, and maintainable code.
• Experience building systems that integrate models with external tools, APIs, databases, and services.
• Ability to operate in ambiguous problem spaces, balancing research-driven approaches with pragmatic product constraints.
• Strong communication skills and comfort working in customer-facing or cross-functional environments.

Nice-to-haves include hands-on experience building AI agents using modern generative AI stacks, experience with agent frameworks, orchestration layers, or workflow systems, familiarity with evaluation, monitoring, and observability for LLM-powered systems in production, and experience deploying ML systems in cloud environments and operating them at scale.

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As an Engineer on the Kubernetes Core Interfaces Team, you’ll design and implement scalable solutions that simplify administration and enhance the user experience of CoreWeave’s Kubernetes platforms. You will develop Helm charts, custom controllers, API endpoints, and other control plane components, while building automation, dashboards, alerts, and testing frameworks. You’ll participate in the on-call rotation and collaborate closely with your teammates in a supportive, high-performance environment that encourages curiosity, ownership, and personal growth.

Some of what you’ll work on:

• Design and implement solutions for scale, fault tolerance, and operational simplicity in CoreWeave’s Kubernetes platforms.

• Develop Helm charts, custom controllers, CRDs, gateways, API endpoints, and other Kubernetes control plane components.

• Build deployment automation, monitoring dashboards, and operational insights for Kubernetes services.

• Participate in the team’s on-call rotation, contributing to incident response and operational excellence.

• Collaborate with teammates to share ideas, provide feedback, and grow together in a high-trust environment.

Who You Are:

• 3+ years of experience in software or infrastructure engineering.

• Experienced in developing fault-tolerant, testable software services, primarily using Go.

• Familiar with Kubernetes concepts and/or experienced administrating Kubernetes clusters.

• Comfortable working with Linux systems, shell scripting, and Linux storage/networking stacks.

• Collaborative, curious, and excited to contribute to a diverse, high-performance team.

Wondering if you’re a good fit? We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams – even if you aren’t a 100% skill or experience match. Here are a few qualities we’ve found compatible with our team. If some of this describes you, we’d love to talk.

• You enjoy solving complex challenges at scale and improving operational workflows.

• You’re curious about cloud infrastructure, Kubernetes, and high-performance systems.

• You thrive in a collaborative environment, sharing knowledge, and learning from teammates.

Why CoreWeave?

At CoreWeave, we work hard, have fun, and move fast! We’re in an exciting stage of hyper-growth that you will not want to miss out on. We’re not afraid of a little chaos, and we’re constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values:

• Be Curious at Your Core

• Act Like an Owner

• Empower Employees

• Deliver Best-in-Class Client Experiences

• Achieve More Together

We support and encourage an entrepreneurial outlook and independent thinking. We foster an environment that encourages collaboration and enables the development of innovative solutions to complex problems. As we get set for takeoff, the organization's growth opportunities are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, too. Come join us!

The base salary range for this role is $109,000 to $160,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility).

What We Offer

The range we’ve posted represents the typical compensation range for this role. To determine actual compensation, we review the market rate for each candidate which can include a variety of factors. These include qualifications, experience, interview performance, and location. In addition to a competitive salary, we offer a variety of benefits to support your needs, including:

• Medical, dental, and vision insurance

• 100% paid for by CoreWeave

• Company-paid Life Insurance

• Voluntary supplemental life insurance

• Short and long-term disability insurance

• Flexible Spending Account

• Health Savings Account

• Tuition Reimbursement

• Ability to Participate in Employee Stock Purchase Program (ESPP)

• Mental Wellness Benefits through Spring Health

• Family-Forming support provided by Carrot

• Paid Parental Leave

• Flexible, full-service childcare support with Kinside

• 401(k) with a generous employer match

• Flexible PTO

• Catered lunch each day in our office and data center locations

• A casual work environment

• A work culture focused on innovative disruption

Our Workplace

While we prioritize a hybrid work environment, remote work may be considered for candidates located more than 30 miles from an office, based on role requirements for specialized skill sets. New hires will be invited to attend onboarding at one of our hubs within their first month. Teams also gather quarterly to support collaboration.

California Consumer Privacy Act - California applicants only

CoreWeave is an equal opportunity employer, committed to fostering an inclusive and supportive workplace. All qualified applicants and candidates will receive consideration for employment without regard to race, color, religion, sex, disability, age, sexual orientation, gender identity, national origin, veteran status, or genetic information. As part of this commitment and consistent with the Americans with Disabilities Act (ADA), CoreWeave will ensure that qualified applicants and candidates with disabilities are provided reasonable accommodations for the hiring process, unless such accommodation would cause an undue hardship. If reasonable accommodation is needed, please contact: careers@coreweave.com.

Export Control Compliance

This position requires access to export controlled information. To conform to U.S. Government export regulations applicable to that information, applicant must either be (A) a U.S. person, defined as a (i) U.S. citizen or national, (ii) U.S. lawful permanent resident (green card holder), (iii) refugee under 8 U.S.C. § 1157, or (iv) asylee under 8 U.S.C. § 1158, (B) eligible to access the export controlled information without a required export authorization, or (C) eligible and reasonably likely to obtain the required export authorization from the applicable U.S. government agency. CoreWeave may, for legitimate business reasons, decline to pursue any export licensing process.

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Our engineering culture values collaboration and building great teams. You will work closely with developers, game studios, and other partners to find opportunities and address challenges towards providing a more rich experience for players while gaming and engaging with online communities.

Key Responsibilities:

• Design, build, and maintain features that help users connect and make friends through gaming on our platform, across desktop and mobile.
• Engage with developers, game studios, and other partners to find opportunities and address challenges towards providing a more rich experience for players while gaming and engaging with online communities.
• Collaborate with Engineers, Designers, Product Owners, and Data Scientists to build engaging, fun, and trusted experiences, while experimenting and iterating on ideas that enhance user interactions.
• Partner with our Content, Marketing, and ML teams to improve ranking and discovery systems, enabling users to find meaningful connections and relevant content.
• Build innovative features that help users discover new friendships and deepen existing ones, creating a trusted and welcoming environment.

Requirements:

• 8+ years of experience as a software engineer.
• Experience with React/TS, Python, or other modern programming languages.
• A track-record of shipping incremental and delightful features that improve the overall user experience.
• Comfortable switching between different technical stacks and learning new ones.
• Enjoy collaborating with product, design, and other stakeholders.
• Take a holistic approach to problem-solving.
• Experience leading projects, gathering requirements, supporting partners, and mentoring others.
• A Discord user who wants to make the product better!

Bonus Points:

• Experience working on a mobile native stack (iOS/Obj-C/Swift), Android (Java, Kotlin)
• Experience integrating or deploying on Steam (or similar platforms)
• Experience using Epic Games Online Services, Steamworks API, Playfab

US base salary range for this full-time position is $248,000 to $279,000 + equity + benefits.

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The Voice Platform team designs and operates the serving systems, streaming pipelines, and APIs that bring Anthropic's audio models from research into production across Claude.ai, our mobile apps, and the Anthropic API. You'll work at the intersection of real-time media, low-latency inference, and distributed systems,building infrastructure where every millisecond of latency is felt by the user.

We partner closely with the Audio research team, who train the speech understanding and generation models, and with product teams shipping voice experiences to users. Your job is to make those models fast, reliable, and delightful to talk to at scale.

Responsibilities:

• Design and build the real-time streaming infrastructure that powers voice conversations with Claude,ingesting microphone audio, orchestrating model inference, and streaming synthesized speech back with minimal latency

• Build low-latency serving systems for speech models, optimizing time-to-first-audio and end-to-end conversational responsiveness

• Develop the public and internal APIs that expose voice capabilities to Claude.ai, mobile clients, and third-party developers

• Own the audio transport layer,codecs, jitter buffers, adaptive bitrate, packet loss recovery,so conversations stay smooth across unreliable networks

• Build observability and quality-measurement systems for voice: latency distributions, audio quality metrics, interruption handling, and turn-taking accuracy

• Partner with Audio research to move new model architectures from experiment to production, and feed real-world performance data back into research

• Collaborate with mobile and product engineering on client-side audio capture, playback, and the end-to-end user experience

You may be a good fit if you

• Have 6+ years of experience building distributed systems, real-time infrastructure, or platform services at scale

• Have shipped production systems where latency is measured in tens of milliseconds and users notice when you miss

• Are comfortable working across the stack,from transport protocols and serving infrastructure up to the APIs product teams build on

• Are results-oriented, with a bias toward flexibility and impact

• Pick up slack, even if it goes outside your job description

• Enjoy pair programming (we love to pair!)

• Care about the societal impacts of voice AI and want to help shape how these systems are developed responsibly

• Are comfortable with ambiguity,voice is a fast-moving space, and you'll help define the architecture as we learn what works

Strong candidates may also have experience with

• Real-time media protocols and stacks: WebRTC, RTP, gRPC bidirectional streaming, or WebSockets at scale

• Audio engineering fundamentals: codecs (Opus, AAC), voice activity detection, echo cancellation, jitter buffering, or audio DSP

• Low-latency ML inference serving, streaming model outputs, or GPU-based serving infrastructure

• Telephony, live streaming, video conferencing, or voice assistant platforms

• Mobile audio pipelines on iOS (AVAudioEngine, AudioUnits) or Android (Oboe, AAudio)

• Working alongside ML researchers to productionize models,speech experience is a plus but not required

Representative projects

• Driving time-to-first-audio below human perceptual thresholds by co-designing the serving pipeline with the Audio research team

• Building a streaming inference orchestrator that interleaves speech recognition, LLM reasoning, and speech synthesis with overlapping execution

• Designing the voice mode API surface for the Anthropic API so developers can build their own voice agents on Claude

• Implementing graceful barge-in and interruption handling so users can cut Claude off mid-sentence naturally

• Instrumenting end-to-end audio quality metrics and building dashboards that catch regressions before users do

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This role is perfect for an engineer who enjoys working close to the metal and across the research boundary. You'll collaborate with researchers and systems architects to bridge algorithmic design with hardware efficiency. You'll prototype new kernel implementations, profile performance across hardware generations, and help define the numerical and parallelism strategies that determine how we scale next-generation AI systems.

Responsibilities

• Design and implement custom ML kernels (e.g., CUDA, CuTe, Triton) for core LLM operations such as attention, matrix multiplication, gating, and normalization, optimized for modern GPU and accelerator architectures.
• Design and think through compute primitives to reduce memory bandwidth bottlenecks and improve kernel compute efficiency.
• Collaborate with research teams to align kernel-level optimizations with model architecture and algorithmic goals.
• Develop and maintain a library of reusable kernels and performance benchmarks that serve as the foundation for internal model training.
• Contribute to infrastructure stability and scalability, ensuring reproducibility, consistency across precision formats, and high utilization of compute resources.
• Document and share insights through internal talks, technical papers, or open-source contributions to strengthen the broader ML systems community.

Skills and Qualifications

Minimum qualifications:

• Bachelor’s degree or equivalent experience in computer science, electrical engineering, statistics, machine learning, physics, robotics, or similar.
• Strong engineering skills, ability to contribute performant, maintainable code and debug in complex codebases
• Understanding of deep learning frameworks (e.g., PyTorch, JAX) and their underlying system architectures.
• Thrive in a highly collaborative environment involving many, different cross-functional partners and subject matter experts.
• A bias for action with a mindset to take initiative to work across different stacks and different teams where you spot the opportunity to make sure something ships.
• Proficiency in CUDA, CuTe, Triton, or other GPU programming frameworks.
• Demonstrated ability to analyze, profile, and optimize compute-intensive workloads.

Preferred qualifications:

• Experience training or supporting large-scale language models with tens of billions of parameters or more.
• Track record of improving research productivity through infrastructure design or process improvements.
• Experience developing or tuning kernels for deep learning frameworks such as PyTorch, JAX, or custom accelerators.
• Familiarity with tensor parallelism, pipeline parallelism, or distributed data processing frameworks.
• Experience implementing low-precision formats (FP8, INT8, block floating point) or contributing to related compiler stacks (e.g., XLA, TVM).
• Contributions to open-source GPU, ML systems, or compiler optimization projects.
• Prior research or engineering experience in numerical optimization, communication-efficient training, or scalable AI infrastructure.

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You'll operate with a high degree of autonomy and will be accountable for setting the long-term technical strategy for the team and executing against it.

As a senior technical leader, you will:

Own and evolve the architecture of Intercom's web stack. Define the long-term technical strategy for the web team, focusing on scalability, performance, developer productivity, observability, and system reliability. Collaborate closely with marketing, design, analytics, and data science stakeholders to ensure the platform supports their goals with accuracy, performance, and agility. Lead and influence the design and implementation of MarTech systems for event tracking, attribution, funnel reporting, A/B testing infrastructure, and more. Partner with engineers across web, infrastructure, and data to create a high-quality, cohesive technical ecosystem. Mentor and elevate engineers across the team and organisation , providing guidance on architecture, data modeling, system design, and engineering best practices. Set the standard for technical excellence in reliability, maintainability, code quality, and operational readiness. Provide technical leadership and insight to Engineering Managers, Product Managers, and executive stakeholders , communicating risks, trade-offs, and opportunities clearly. Contribute hands-on to the codebase , leading by example and helping unblock and accelerate key projects.

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Your measure of success is the number of workflows you've permanently transformed and the extent to which those in your group start any task with an AI tool.

Responsibilities:

• Identify and document the highest-leverage workflow transformations within your group's day-to-day work by deeply understanding their processes and outputs
• Build custom tools, agents, automations, and skills tailored to each marketer's specific responsibilities
• Coach and partner with each marketer through a progressive journey: from awareness, to first win, to regular AI integration, to full workflow transformation, to self-sufficiency
• Teach marketers to build and iterate on their own tools over time, creating independence
• Recognize patterns across your cohort and systematically scale what works , a tool built for one marketer should become reusable for their peers
• Document every tool, playbook, and transformation pattern you build so the entire FDA team can use each other's work
• Share wins visibly within your cohort and with leadership to build momentum, inspire, and celebrate success
• Track individual and cohort progress rigorously against a defined maturity model, moving every marketer toward self-sustaining, AI-first work
• Prepare marketers for an agentic future , not just prompt writing, but designing, building, and overseeing autonomous, multi-agent workflows

Who you are:

We're looking for people who have already lived the transformation they'll be driving for others. You've used AI to fundamentally change how you work , not as a novelty, but as your default operating mode.

• You are a deep AI practitioner. You build agents, automations, and tools fluently. You don't just know what AI can do in theory , you've built things that changed how real work gets done. You can build in real time alongside the people you support.
• You are an exceptional coach and communicator. You can meet people wherever they are. You create desire for progress, and you adapt your approach to each person.
• You understand marketing work. You either have direct experience in marketing or can quickly learn the workflows, deliverables, tools, and pressures of your assigned group. You know that understanding someone's work is a prerequisite to transforming it.
• You are a pattern recognizer. When you build something that works for one person, you immediately see how it applies to others. You think in systems, not one-off solutions.
• You are high-caliber, persistent, and versatile. Your skills and experience are valuable across the company. You're the kind of person who could succeed in many roles at Stripe.
• You bias toward action and speed. You'd rather show someone a working proof-of-concept on their own deliverable today than present a polished deck about what's theoretically possible next quarter.
• You are comfortable with ambiguity and evolution. This is a new team building a new operating model. The playbook will be rewritten as we learn. You thrive in that environment.

Minimum requirements:

• 5+ years of professional experience in a role requiring analytical thinking, problem-solving, and cross-functional collaboration
• Demonstrated, hands-on experience building AI-powered tools, agents, automations, or workflows that transformed real work processes (not just using AI as a chatbot , building with it)
• Track record of coaching, teaching, or enabling others , formally or informally , with evidence that people you've helped actually changed how they work
• Strong written and verbal communication skills, with the ability to explain technical concepts to non-technical audiences and adapt your style to different learners
• Comfort working across multiple workstreams and relationships simultaneously (you'll be supporting ~20 marketers at varying stages of their AI journey)

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Your responsibilities will include:

• Prototyping apt technical solutions and finding best fits for the context engine.
• Architecting and building the core Context Platform.
• Designing schemas and primitives for Decision Memory and enterprise context.
• Owning context storage systems (graph, vector, event/time-based).
• Building read/write/query APIs used by agents, products, and external apps.
• Designing permission-aware, auditable context access.

You will be working closely with agentic systems engineers and product leadership to ensure the context engine is interoperable, portable, and zero-lock-in by design.

In this role, you will own:

• Context schemas and schema evolution strategies.
• Storage and data modeling choices.
• Platform APIs and interfaces.
• Security, identity propagation, and audit foundations.
• Long-term scalability and correctness of context data.

You will not own:

• Agent behavior or orchestration logic.
• Business rules or governance policy decisions.
• Product UI or workflow automation.

The ideal candidate will have significant experience building distributed systems, data platforms, or infrastructure, and will be comfortable operating in ambiguous, greenfield problem spaces. They will also have deep expertise in data modeling and schema design, experience designing shared platforms used by many teams, and strong instincts around APIs, contracts, and backward compatibility.

Nice to have experience with knowledge graphs, metadata systems, or search/retrieval systems, experience building systems with governance, auditability, or compliance requirements, and familiarity with dbt or modern analytics stacks or developer tooling.

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Key Responsibilities:

• Team Leadership & Mentorship: Hire, lead, coach, and develop a high-performing team of product and marketing analysts.
• Analytics Strategy & Execution: Own the company's marketing measurement, experimentation, and insight generation for paid, owned, and integrated channels, and for performance across acquisition, activation, engagement, retention, and LTV.
• Hands-On Analysis: Perform deep-dive analyses to uncover insights that inform product and business decisions.
• Cross-Functional Collaboration: Act as a strategic thought partner to identify opportunities, measure success, and optimize Marketing and product performance.

Requirements:

• 10+ years of experience in analytics, with at least 2 years in a people management role.
• Strong technical skills in SQL, Python, data visualization tools (Amplitude, Tableau) and experimentation.
• Has direct experience in marketing analytics using Media Mix Models (MMM), difference-in-differences and other causal inference techniques.
• Proven track record of leading high-performing marketing or product analytics teams.
• Excellent communication and storytelling skills.
• Ability to balance strategic thinking with hands-on execution.

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You'll serve as a technical anchor for the team, working closely with your engineering manager, product manager, and partners across Site Reliability Engineering, Release, Security, and Development to shape cloud-native, operator-driven deployment patterns that reduce operational complexity and upgrade friction.

In your first year, you'll help define the architecture for zero-downtime upgrades, strengthen observability and reliability practices, and guide the next generation of deployment automation for self-managed GitLab environments.

Some examples of our projects:

• Evolving GitLab Operator and Helm charts to support zero-downtime upgrades for complex, stateful GitLab installations

• Advancing the GitLab Environment Toolkit to simplify large-scale, production-ready self-managed deployments

Responsibilities

• Guide the technical vision and architecture for GitLab's cloud-native, self-managed deployments and upgrade workflows.

• Establish operational maturity standards, service integration patterns, and deployment models that help development teams manage the lifecycle of their components.

• Design and maintain Kubernetes Operators, Helm charts, and upgrade orchestration tooling for self-managed GitLab deployments across varied environments.

• Develop automation and integration frameworks for database migrations, rolling deployments, compatibility checks, and rollback paths.

• Define database and application lifecycle strategies, including safe PostgreSQL migration approaches and validation mechanisms that reduce downtime risk.

• Work with Product Management, GitLab.com Site Reliability Engineering, GitLab Dedicated, and development teams to align deployment patterns with customer needs.

• Mentor engineers and enable customer-facing teams through design reviews, code reviews, documentation, and runbooks.

• Drive observability, testing, performance, and resilience practices for self-managed deployments, and contribute to incident response and post-incident learning.

Requirements

• Strong software engineering experience designing and delivering production systems that customers install and operate in their own infrastructure.

• Proficiency in Go for large, complex codebases, with familiarity with Ruby on Rails and Rails application architecture as a useful addition.

• Hands-on experience with Kubernetes in production, including building and maintaining Operators, designing Helm charts for stateful applications, and working with Custom Resource Definitions, admission controllers, and controller patterns.

• Knowledge of cloud-native systems and tooling, such as service mesh, observability stacks, infrastructure as code, and automation tools like Terraform or Ansible.

• Experience with stateful workloads and databases, including PostgreSQL schema design and migrations, persistent volumes, storage classes, and approaches for reducing downtime during upgrades.

• Understanding of Linux systems and production operations, including package management, systemd, system-level debugging, observability, incident response, and on-call participation.

• Ability to guide through influence, including writing clear technical proposals, documenting decisions, mentoring engineers, and working effectively across teams.

• Interest in open source infrastructure or deployment tooling, or transferable experience from adjacent domains, with the ability to explain technical concepts clearly to different audiences.

About the Team

The Delivery - Upgrades team sits within GitLab Delivery and focuses on delivering GitLab to self-managed users through supported, validated deployment tooling. We own and evolve the GitLab Omnibus package, Helm charts, GitLab Operator, and the GitLab Environment Toolkit, and we work asynchronously across regions with partners in Site Reliability Engineering, Release, Security, and Development.

Our work centers on enabling zero-downtime upgrades, reducing operational complexity at scale, supporting GitLab’s cloud-native transition while continuing to serve existing deployments, and improving the upgrade experience for customers running GitLab in diverse environments.

For more on how we work, see [Link: Team Handbook Page].

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CoreWeave is The Essential Cloud for AI™. Built for pioneers by pioneers, CoreWeave delivers a platform of technology, tools, and teams that enables innovators to build and scale AI with confidence. Trusted by leading AI labs, startups, and global enterprises, CoreWeave combines superior infrastructure performance with deep technical expertise to accelerate breakthroughs and turn compute into capability. Founded in 2017, CoreWeave became a publicly traded company (Nasdaq: CRWV) in March 2025.

About the Role

Production Engineering ensures CoreWeave’s cloud delivers world-class reliability, performance, and operational excellence. We are hiring a Senior Production Engineer to take direct, hands-on ownership of critical tooling that drives reliability and delivery success.

In this role, you will work broadly across the cloud stack designing, implementing, deploying, and operating systems that improve delivery velocity, service availability, and operational safety. You’ll be responsible for leading end-to-end technical projects, maintaining long-lived systems the team owns, and strengthening our operational foundations through durable engineering investments.

This is a role for someone who enjoys building, debugging, and operating production systems. You will collaborate closely with service owners, but your primary impact comes from the reliability, quality, and maturity of the systems you deliver and maintain over time.

What You’ll Do

• Take hands-on ownership of critical systems and frameworks, driving their architecture, implementation, and long-term evolution.

• Lead end-to-end delivery of engineering projects that improve availability, scalability, operational automation, and failure recovery.

• Build and maintain observability, alerting, automated remediation, and resilience testing for the systems you support.

• Participate in incident response as a subject-matter expert; drive deep root-cause investigations and implement lasting fixes.

• Improve runbooks, sources of truth, deployment workflows, and operational tooling to harden production readiness.

• Eliminate single points of failure and reduce operational toil through automation, refactors, and system redesigns.

• Ship production code regularly in Python, Go, or similar languages, and participate in on-call rotations.

• Maintain and mature long-term projects and frameworks owned by the team, ensuring they remain reliable, well-instrumented, and easy to operate.

• Collaborate with platform teams to ensure new features and services integrate cleanly with our reliability best-practices and tooling.

What You’ve Worked On (Minimum Qualifications)

• 7+ years of engineering experience building and operating distributed systems or cloud platforms.

• Demonstrated ability to debug complex production issues end-to-end, across services, infrastructure layers, and automation.

• Strong programming or scripting ability (Python, Go, or similar), with experience shipping and operating production services and tools.

• Deep knowledge of cloud-native technologies and distributed system patterns, particularly Kubernetes.

• Experience with modern observability stacks: metrics, tracing, structured logs, SLOs/SLIs, and incident lifecycle practices.

• A track record of successfully delivering hands-on reliability improvements through engineering execution.

Preferred Qualifications

• Experience building internal tooling, frameworks, or automation that supports high-availability cloud operations.

• Familiarity with DR/BCP, service tiering, capacity planning, or chaos engineering.

• Background operating or building large-scale AI or GPU-accelerated infrastructure.

• Experience maintaining multi-year ownership of foundational production systems.

Why CoreWeave?

At CoreWeave, we work hard, have fun, and move fast! We’re in an exciting stage of hyper-growth that you will not want to miss out on. We’re not afraid of a little chaos, and we’re constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values:

• Be Curious at Your Core

• Act Like an Owner

• Empower Employees

• Deliver Best-in-Class Client Experiences

• Achieve More Together

We support and encourage an entrepreneurial outlook and independent thinking. We foster an environment that encourages collaboration and enables the development of innovative solutions to complex problems. As we get set for takeoff, the organization's growth opportunities are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, too. Come join us!

The base salary range for this role is $139,000 to $204,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility).

What We Offer

The range we’ve posted represents the typical compensation range for this role. To determine actual compensation, we review the market rate for each candidate which can include a variety of factors. These include qualifications, experience, interview performance, and location.

In addition to a competitive salary, we offer a variety of benefits to support your needs, including:

• Medical, dental, and vision insurance - 100% paid for by CoreWeave

• Company-paid Life Insurance

• Voluntary supplemental life insurance

• Short and long-term disability insurance

• Flexible Spending Account

• Health Savings Account

• Tuition Reimbursement

• Ability to Participate in Employee Stock Purchase Program (ESPP)

• Mental Wellness Benefits through Spring Health

• Family-Forming support provided by Carrot

• Paid Parental Leave

• Flexible, full-service childcare support with Kinside

• 401(k) with a generous employer match

• Flexible PTO

• Catered lunch each day in our office and data center locations

• A casual work environment

• A work culture focused on innovative disruption

Our Workplace

While we prioritize a hybrid work environment, remote work may be considered for candidates located more than 30 miles from an office, based on role requirements for specialized skill sets. New hires will be invited to attend onboarding at one of our hubs within their first month. Teams also gather quarterly to support collaboration.

California Consumer Privacy Act - California applicants only

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You will also be an integral part of achieving industry-leading end-to-end performance benchmarking publications: If MLPerf (Training & Inference), Working closely with NVIDIA (Megatron-LM, TensorRT-LLM & DGX cloud) and the open-source community (llm-d, vLLM and all popular ML frameworks) speak to you, come help us demonstrate CoreWeave's performance reliability leadership in the field.

Responsibilities

• Strategy & Leadership - Define the multi-year benchmarking strategy and roadmap; prioritize models/workloads (LLMs, diffusion, vision, speech) and hardware tiers. Build, lead, and mentor a high-performing team of performance engineers and data analysts. Establish governance for claims: documented methodologies, versioning, reproducibility, and audit trails.

• Perf Ownership - Lead end-to-end MLPerf Inference and Training submissions: workload selection, cluster planning, runbooks, audits, and result publication. Coordinate optimization tracks with NVIDIA (CUDA, cuDNN, TensorRT/TensorRT-LLM, Triton, NCCL) to hit competitive results; drive upstream fixes where needed.

• Internal Latency & Throughput Benchmarks - Design a Kubernetes-native, repeatable benchmarking service that exercises CoreWeave stacks across SUNK (Slurm on Kubernetes), Kueue, and Kubeflow pipelines. Measure and report p50/p95/p99 latency, jitter, tokens/s, time-to-first-token, cold-start/warm-start, and cost-per-token/request across models, precisions (BF16/FP8/FP4), batch sizes, and GPU types. Maintain a corpus of representative scenarios (streaming, batch, multi-tenant) and data sets; automate comparisons across software releases and hardware generations.

• Tooling & Automation - Build CI/CD pipelines and K8s controllers/operators to schedule benchmarks at scale; integrate with observability stacks (Prometheus, Grafana, OpenTelemetry) and results warehouses. Implement supply-chain integrity for benchmark artifacts (SBOMs, Cosign signatures).

• Cross-functional & Community - Partner with NVIDIA, key ISVs, and OSS projects (vLLM, Triton, KServe, PyTorch/DeepSpeed, ONNX Runtime) to co-develop optimizations and upstream improvements. Support Sales/SEs with authoritative numbers for RFPs and competitive evaluations; brief analysts and press with rigorous, defensible data.

Requirements

• 10+ years building distributed systems or HPC/cloud services, with deep expertise on large-scale ML training or similar high-performance workloads.

• Proven track record of architecting or building planet-scale data systems (e.g., telemetry platforms, observability stacks, cloud data warehouses, large-scale OLAP engines).

• Deep understanding of GPU performance (CUDA, NCCL, RDMA, NVLink/PCIe, memory bandwidth), model-server stacks (Triton, vLLM, TensorRT-LLM, TorchServe), and distributed training frameworks (PyTorch FSDP/DeepSpeed/Megatron-LM).

• Proficient with Kubernetes and ML control planes; familiarity with SUNK, Kueue, and Kubeflow in production environments.

• Excellent communicator able to interface with executives, customers, auditors, and OSS communities.

Nice to have

• Experience with time-series databases, log-structured merge trees (LSM), or custom storage engine development.

• Experience running MLPerf submissions (Inference and/or Training) or equivalent audited benchmarks at scale.

• Contributions to MLPerf, Triton, vLLM, PyTorch, KServe, or similar OSS projects.

• Experience benchmarking multi-region fleets and large clusters (thousands of GPUs).

• Publications/talks on ML performance, latency engineering, or large-scale benchmarking methodology.

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You'll bring a blend of data-driven strategy, operational rigor, and audience insight to drive measurable impact across multiple channels and audiences. Partnering closely with Product Marketing, RevOps, and Sales, you'll architect scalable programs that educate the market, position Descript as an industry leader, and deliver efficient pipeline acceleration.

Key responsibilities include:

• Building and leading the overall demand generation and growth marketing strategy, across enterprise and self-serve segments, aligning to Descript's GTM and revenue goals.
• Developing and improving the systems we use to scale pipeline generation, ensuring marketing is consistently feeding our growing sales organization.
• Owning MQLs: direct and execute integrated, multi-channel campaigns that incorporate product positioning, audience insights, and creative from fellow marketing team members.
• Partnering with leadership across Marketing, Sales, and RevOps to drive alignment on funnel KPIs; build the learning loops that power continuous improvement in our strategy, tool stack, and creative execution for awareness, nurture, and conversion.
• Mentoring and managing a team of growth marketing professionals.
• Enhancing marketing automation, lead scoring, and reporting.

We're looking for someone with:

• 10+ years of experience in B2B SaaS demand generation or growth marketing, with at least 3–5 years in a leadership role managing teams.
• A proven track record of delivering pipeline and revenue growth.
• Deep expertise across acquisition, engagement, and nurture channels - including paid social, email, content syndication, and partnerships.
• Advanced knowledge of AI-powered marketing stacks and automation workflows.
• Analytical mindset with strong command of marketing metrics, attribution, and forecasting.
• Exceptional collaboration and communication skills; able to influence cross-functional stakeholders and present to executives.
• Strategic thinker with a bias for action - able to translate insights into scalable, creative programs that drive measurable outcomes.

The base salary range for this role is $203,000-230,000.

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We are seeking senior software engineers with specialization in database and stream processing who can help us fulfill the goal of our global datastore strategy and establish communication models for our data flow. This individual will work with a team of mixed skilled engineers and have the opportunity to work on the full range of rewarding challenges that come with the business of building a cloud in a communicative, supportive, and high-performing environment.

As a member of the Data Platform Team you will have the opportunity to:

• Design and implement the platform to deliver data to teams with a focus on providing managed solutions through APIs
• Participate in operations and scaling of relational data platforms
• Develop a stream processing architecture and solve for scalability and reliability
• Improve the performance, security, reliability, and scalability of our data platforms and related services, and participate in the team’s on-call rotation
• Establish guidelines and guard rails for data access and storage for stakeholder teams
• Ensure compliance with standards for data protection regulation
• Grow, change, invest in your teammates, be invested-in, share your ideas, listen to others, be curious, have fun, and, above all, be yourself

The ideal candidate will have 5+ years of experience in a software or infrastructure engineering industry, with experience operating services in production and at scale and familiarity with reliability engineering concepts such as different types of testing, progressive deployments, error budgets, observability, and fault-tolerant design.

The base salary range for this role is $175,000 to $210,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location.

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This is a rare opportunity to architect and build distributed systems that will fundamentally change how large organisations approach application security and developer security workflows.

As the SRM Stage Lead, you'll be responsible for transforming our engineering culture toward high-performance distributed systems while delivering an exceptional user experience for both Application Security professionals and Developers.

You'll own the technical strategy for processing, analysing, and remediating vulnerabilities across massive codebases and complex enterprise environments.

Technical Leadership & Architecture

• Design distributed systems architecture capable of processing vulnerability data from thousands of repositories, millions of commits, and complex dependency graphs in real-time
• Drive storage system decisions for multi-petabyte security datasets, balancing query performance, cost efficiency, and data retention requirements across time-series, graph, and document storage paradigms
• Architect scalable analysis pipelines that can ingest vulnerability feeds, correlate findings across multiple security tools, and provide actionable intelligence to both security teams and individual developers
• Lead the technical evolution from monolithic security scanning to microservices-based, event-driven vulnerability management systems

Engineering Culture Transformation

• Champion high-performance systems thinking throughout the team, establishing patterns for horizontal scaling, efficient resource utilisation, and fault-tolerant distributed computing
• Establish technical standards for system observability, chaos engineering, and performance optimisation in security-critical systems
• Mentor and develop senior engineers in distributed systems design, database optimisation, and large-scale system architecture
• Drive architectural decision records (ADRs) for major technical decisions, particularly around data storage, processing frameworks, and system boundaries

Product & User Experience Excellence

• Own the end-to-end user journey (in partnership with PM) for both AppSec professionals managing enterprise-wide risk and developers receiving actionable security feedback in their workflow
• Design APIs and interfaces that abstract complexity while providing the power and flexibility that security professionals demand
• Collaborate with Product Management, UX and Product Design to translate complex technical capabilities into intuitive user experiences
• Establish feedback loops with large enterprise customers to ensure our technical solutions scale with their organisational complexity

Strategic Technical Execution

• Evaluate and integrate cutting-edge technologies in areas such as graph databases, stream processing, machine learning inference at scale, and distributed caching, in collaboration with GitLab’s Infrastructure, Data and AI teams
• Own the technical roadmap for vulnerability correlation, risk scoring, and automated remediation workflows
• Drive partnerships with other GitLab stages to ensure seamless integration across the DevSecOps platform
• Lead incident response for availability and performance issues in customer-facing security systems

What You’ll Bring

• 10+ years of software engineering experience with 5+ years leading distributed systems at scale (>100M daily operations)
• Deep expertise in designing and operating high-throughput, low-latency distributed systems with complex data models
• Proven experience with polyglot persistence strategies, including relational databases (PostgreSQL, Cloud Spanner), time-series databases, graph databases, and distributed key-value stores
• Strong background in stream processing frameworks (Apache Kafka, Apache Flink, or similar) and event-driven architectures
• Hands-on experience with container orchestration (Kubernetes) and cloud-native observability stacks
• Security domain knowledge with understanding of vulnerability assessment, static analysis, dependency scanning, or application security testing

Leadership & Communication

• Proven track record of leading and growing high-performing engineering teams (40+ engineers)
• Experience transforming engineering culture and establishing technical excellence standards in fast-growing organisations
• Strong technical communication skills with ability to present complex architectural decisions to executive stakeholders
• Collaborative leadership style with experience working across multiple engineering teams and product stakeholders

Problem-Solving & Innovation

• Systems thinking approach to complex technical problems with demonstrated ability to make appropriate trade-offs between performance, scalability, and maintainability
• Experience with A/B testing frameworks and data-driven decision making in technical contexts
• Track record of successfully delivering large-scale technical migrations or architectural transformations
• Startup or high-growth company experience with ability to balance technical debt with rapid feature delivery

About the team

Security Risk Management sits at the heart of modern DevSecOps. The systems you build will directly impact how Fortune 500 companies protect their applications and how millions of developers integrate security into their daily workflow.

You'll have the opportunity to define the future of application security tooling while working with some of the most challenging distributed systems problems in the industry.

The Technical Challenge

You'll be solving some of the most interesting distributed systems problems in the security space:

• Scale: Processing vulnerability data for organisations with 100,000+ repositories and millions of developers
• Performance: Sub-second query response times for complex security analytics across massive datasets
• Reliability: 99.95%+ uptime SLAs for security-critical workflows that can't afford downtime
• Complexity: Correlating findings across 20+ different security tools while maintaining data lineage and audit trails
• User Experience: Making complex security data accessible to both security experts and developers with varying security expertise

Salary

The base salary range for this role’s listed level is currently for residents of the United States.

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Key responsibilities include:

• Lead design reviews and drive architecture within the team; decompose multi-service work into clear milestones.
• Define and own SLIs/SLOs; ensure post-incident actions land and reliability improves release-over-release.
• Implement advanced optimizations (e.g., micro-batch schedulers, speculative decoding, KV-cache reuse) and quantify impact.
• Strengthen incident posture: capacity planning, autoscaling policy, graceful degradation, rollback/traffic-shift strategies.
• Mentor IC1/IC2 engineers; review cross-team designs and elevate coding/testing standards.

Requirements include:

• 3-5 years of industry experience building distributed systems or cloud services.
• Strong coding in Python or Go (C++ a plus) and deep familiarity with networked systems and performance.
• Hands-on experience with Kubernetes at production scale, CI/CD, and observability stacks (Prometheus, Grafana, OpenTelemetry).
• Practical knowledge of inference internals: batching, caching, mixed precision (BF16/FP8), streaming token delivery.
• Proven track record improving tail latency (P95/P99) and service reliability through metrics-driven work.

Preferred qualifications include contributions to inference frameworks, experience with CUDA kernels, NCCL/SHARP, RDMA/NUMA, or GPU interconnect topologies, and leading multi-team initiatives or partnering with customers on mission-critical launches.

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In this role, you will:

• Establish and lead the SRE / production engineering practice for the Common Services organization, including standards for reliability, incident management, and on-call, in partnership with the central Product Engineering organization.
• Develop an Operational Excellence strategy that focuses on not only improving system performance but also monitoring and reducing operational toil
• Partner with engineering and product teams to define SLOs, SLIs, and error budgets for critical Common Services, and ensure these become part of how teams plan and make tradeoffs.
• Own and improve the incident management lifecycle for Common Services, including on-call rotations, escalation paths, incident tooling, post-incident reviews, and follow-through on corrective actions.
• Drive the observability strategy (metrics, logs, traces, dashboards, alerts) for Common Services, ensuring we have actionable visibility into the health, performance, and capacity of key systems.
• Collaborate with engineering leads to design and review architectures for reliability, scalability, resilience, and operability, including failure modes, redundancy, and graceful degradation.
• Lead efforts to automate and harden operational workflows, including deployments, rollbacks, configuration management, change management, and routine maintenance tasks.
• Build strong, trust-based relationships with partner teams and stakeholders, becoming a go-to leader for production readiness and operational risk within Common Services.
• Hire, mentor, and develop SRE and production engineering talent, fostering a culture of continuous improvement, learning from incidents, and humane on-call.
• Partner with other SRE and production engineering leaders across CoreWeave to align on global practices, tools, and reliability goals, representing the needs and constraints of Common Services.

You will be responsible for defining the reliability strategy, processes, and standards for the Common Services portfolio and driving consistent, high-quality operational practices across multiple teams.

The base salary range for this role is $206,000 to $303,000.

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This role blends research and engineering responsibilities, requiring you to both implement novel approaches and contribute to research direction. You'll work on fundamental research in reinforcement learning, designing training environments and methodologies that push the state of the art, and building evaluations that measure genuine capability.

Responsibilities:

• Build the next generation of agentic environments
• Build rigorous evaluations that measure real capability
• Collaborate across research and infrastructure teams to ship environments into production training
• Debug and iterate rapidly across research and production ML stacks
• Contribute to research culture through technical discussions and collaborative problem-solving

You may be a good fit if you:

• Are highly impact-driven , you care about outcomes, not activity
• Operate with high agency
• Have good research taste or senior technical experience, demonstrating good judgment in identifying what actually matters in complex problem spaces
• Can balance research exploration with engineering implementation
• Are passionate about the potential impact of AI and are committed to developing safe and beneficial systems
• Are comfortable with uncertainty and adapt quickly as the landscape shifts
• Have strong software engineering skills and can build robust infrastructure
• Enjoy pair programming (we love to pair!)

Strong candidates may also have one or more of the following:

• Have industry experience with large language model training, fine-tuning or evaluation
• Have industry experience building RL environments, simulation systems, or large-scale ML infrastructure
• Senior experience in a relevant technical field even if transitioning domains
• Deep expertise in sandboxing, containerization, VM infrastructure, or distributed systems
• Published influential work in relevant ML areas

The annual compensation range for this role is $500,000-$850,000 USD.

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Reporting to a senior engineering manager, you will combine people leadership with technical guidance, helping shape team processes, execution, and culture while partnering closely with hardware, platform, and operations teams.

Key Responsibilities:

• Lead & support the team – manage, mentor, and coach a small team of firmware engineers through regular 1-on-1s, goal-setting, and feedback, fostering a collaborative and psychologically safe environment.

• Execution & delivery – help plan and track firmware development work, ensuring timely delivery of features, bug fixes, and platform enablement across multiple hardware programs.

• Technical guidance – participate in design discussions and reviews, helping the team make sound technical decisions around embedded firmware, BMC architectures, and system integration.

• Cross-functional collaboration – work closely Hardware Engineering and Systems Engineering teams to ensure firmware aligns with hardware requirements and production needs.

• Quality & reliability – support best practices around testing, validation, debugging, and documentation to ensure firmware reliability in large-scale production environments.

• Process building – help establish lightweight development processes, documentation standards, and tooling appropriate for a growing firmware organization.

• Grow the team – partner with recruiting and senior leadership to interview and onboard new firmware engineers as the team scales.

• Communicate & align – provide clear status updates, surface risks early, and communicate trade-offs and progress to stakeholders and leadership.

Requirements:

• 2+ years of experience in an engineering leadership role (engineering manager, tech lead with people management responsibilities, or similar).

• Prior hands-on experience as a firmware or embedded systems engineer.

• Working knowledge of embedded firmware development using C/C++ in Linux-based environments.

• Familiarity with BMC firmware stacks such as OpenBMC and/or AMI MegaRAC/SPX.

• Understanding of hardware interfaces and system-level concepts (e.g., I2C, SPI, UART, board bring-up).

• Strong communication skills, with the ability to collaborate across hardware and software teams.

• Passion for mentoring engineers and building inclusive, high-performing teams.

Preferred Qualifications:

• Experience supporting firmware development for data center or server-class hardware.

• Familiarity with Redfish, IPMI, or other data center management protocols.

• Exposure to firmware testing, validation, and production bring-up processes.

• Experience helping establish engineering processes in a new or growing team.

• Background in fast-growing or hardware-software integrated environments.

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Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organisations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence.

This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk.

About the Team

At Okta, our motto is "Always On." Within the Technical Operations (TechOps) team, we live this mission by building the most reliable and performant systems on the planet. We empower organisations to do their most significant work by securely connecting any person, on any device, to the technologies they need.

The Role

We are seeking a Senior Site Reliability Engineer (SRE) to lead the evolution of our large-scale production systems. This role is designed for a technical expert who thrives on solving complex problems at scale and lives by the ethic: "If you have to do it twice, automate it." Based in the Washington, D.C. area, you will ensure our infrastructure maintains uncompromising reliability and performance while supporting critical national security missions in secure, restricted environments.

Security Requirement: Must be able to obtain and maintain a U.S. security clearance (Secret or Top Secret) to the extent required by U.S. Government contracts.

The selected candidate may be subject to drug testing to the extent required by U.S. Government contracts.

What You’ll Do

• Infrastructure Leadership: Design, build, and oversee Okta’s production infrastructure, ensuring architectural integrity and peak performance.

• Incident Engineering: Act as a senior escalation point for production incidents, conducting deep-dive root cause analysis and implementing permanent, automated preventive solutions.

• Strategic Automation: Eliminate manual toil by developing sophisticated automation frameworks, evolving monitoring tools, and establishing rigorous technical documentation.

• System Resilience: Optimize a highly available, large-scale environment, ensuring "Always On" service delivery across complex network topologies.

• Mentorship: Provide technical guidance to the engineering organisation, championing SRE best practices and a culture of self-education.

What You’ll Bring

Core Requirements

• Clearance: Active TS/SCI with Polygraph.

• Compliance Expertise: Deep professional experience with FedRAMP and DoD IL6 frameworks.

• Education: B.S. in Computer Science or equivalent technical experience.

Technical Expertise

• Networking & Cloud Architecture: Mastery of AWS networking and security, including Transit Gateways, VPCs, Route Tables, ELBs, and NACLS.

• Infrastructure as Code (IaC): Advanced experience automating enterprise-scale infrastructure via Terraform or CloudFormation.

• Systems & Scripting: Expert-level Linux systems administration with proficiency in Go, Python, Bash, or Ruby.

• Production Support: Proven success managing Docker containers and Java-based stacks (Apache/Tomcat) in high-security production environments.

Protocol Knowledge: Solid understanding of networking concepts, IP protocols, and multi-cloud infrastructure.

#LI-TM

#LI-Hybrid

P24505

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Your primary responsibilities will include delivering interactive presentations and solution demonstrations to all levels of an organization, whiteboarding solutions, and leading Q&A sessions with prospective customers. You will also collaborate with account executives to develop and execute territory and account strategies to maximize the Okta opportunity in those accounts.

To be successful in this role, you will need to have a strong technical understanding of the Auth0 product line and the underlying technologies and protocols. You should also be able to communicate effectively with both technical and non-technical audiences.

In addition to your technical expertise, you will need to have excellent communication and interpersonal skills, as well as the ability to work in a fast-paced environment.

As a Solutions Engineer, you will have the opportunity to work with a variety of customers and projects, and to contribute to the growth and success of our business.

If you are a motivated and detail-oriented individual with a passion for technology and customer service, we encourage you to apply for this exciting opportunity.

The annual On Target Compensation (OTE) range for this position for candidates located in Germany is between €122,000-€134,000 EUR.

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You will embed directly with our strategic accounts, large enterprises with complex data needs, often in financial services, insurance, and other regulated industries. You will work alongside their teams to understand their go-to-market challenges, then design and deliver bespoke intelligence applications that combine our third-party data with the customer's first-party data to drive real business outcomes.

You will own the engagement end-to-end: from discovery through deployment, from executive presentation through production code. You will work closely with our data and product teams to bring the full breadth of our data foundation to bear , company intelligence, contact data, buying signals, intent data, and specialized vertical datasets , assembled into purpose-built applications tailored to each customer's specific personas and workflows.

You will have access to incredible data, powerful infrastructure, and our most important customer relationships. What you build with them , and how you build it , will define the model going forward.

Responsibilities:

• Build the FDE Playbook
• Document what works: onboarding sequences, deployment patterns, integration frameworks, success metrics
• Feed field learnings back to product, engineering, and data teams to inform product direction and dataset priorities
• Own Strategic Customer Engagements End-to-End
• Serve as the primary technical point of contact for assigned strategic accounts
• Run discovery sessions, scope use cases, design solutions, build applications, and deploy them in the customer's environment
• You own the outcome , not just the delivery
• Deliver Custom Intelligence Applications
• Build bespoke 'single pane of glass' applications that unify our data with the customer's proprietary data
• These are purpose-built for specific personas and workflows , not configured off-the-shelf products
• Bridge Technical and Business Audiences
• Sit with the sales team
• Present to executive leadership
• Synthesize complex go-to-market data needs into clear, actionable proposals , then deliver the solution
• You're equally comfortable whiteboarding architecture with a data engineering team and presenting ROI to a CRO
• Drive Stickiness and Expansion
• Every application you build makes our data more deeply embedded in the customer's daily workflows
• Identify expansion opportunities as they emerge , new use cases, new personas, new datasets

Requirements:

• High Ownership, High Ambiguity Tolerance
• This role doesn't exist yet at ZoomInfo. You take ownership of outcomes , not tasks , and you're comfortable making judgment calls with incomplete information, building process where there is none, and figuring things out as you go
• Strong Software Engineering Fundamentals
• You write production-quality code
• You're proficient in Python, SQL, and modern web frameworks
• You're comfortable with APIs, data pipelines, cloud platforms (AWS, GCP, or Azure), and building applications that real users depend on daily
• Familiarity with API tooling , GraphQL, REST, Postman, authentication patterns (JWT, OAuth) , is a plus; deep expertise isn't required, but you should be comfortable navigating and integrating against APIs quickly
• You work fluently in LLM-based development environments like Claude Code or Codex , these are core tools in how we build, not a nice-to-have
• Customer-Facing Communication
• You've worked directly with customers in a technical capacity , solutions engineering, consulting, technical account management, or a previous FDE role
• You can synthesize complex data needs for an executive audience and discuss architecture with an engineering team in the same meeting
• You're comfortable navigating enterprise environments with competing stakeholders and priorities
• Go-to-Market Data Familiarity (Preferred)
• Experience working with B2B data, CRM systems, sales/marketing tech stacks, or similar go-to-market infrastructure
• You understand what it means to operationalize data in a revenue context

Why This Role

• The mandate is clear. Driving data consumption and growth across ZoomInfo's strategic accounts is a top company priority
• We already have working prototypes, validated customer demand, and executive sponsorship
• The data team, product team, and infrastructure are in place
• What's needed is the person who executes
• Enterprise customer access. ZoomInfo's customer base includes market-leading GTM organizations at some of the largest enterprises in the world
• You'll be embedded with these teams, solving real problems with meaningful budgets and complex data needs
• Best-in-class data and infrastructure. ZoomInfo's data foundation, GTM Data Store, query infrastructure, and vertical dataset catalog give you the raw materials to build custom intelligence applications that aren't possible anywhere else

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Location: Remote-USA

The Payments team at Airbnb is responsible for everything related to settling money in Airbnb's global marketplace. As a Senior Machine Learning Engineer for Payments, you will be the catalyst that transforms bold AI innovation into production systems that make Airbnb Payment experience feel effortless and secure.

Responsibilities:

• Spearhead LLM agents, real-time anomaly detectors, and other breakthrough solutions that solve real-world problems and create product magic.

• Collaborate with product, engineering, ops, and data science to spot high-leverage opportunities, refine AI/ML requirements, make principled architecture choices, and measure business value with clear, data-driven metrics.

• Design, train, deploy, and operate large-scale AI applications for both batch and streaming workloads, ensuring low latency, high reliability, and continuous improvement via automated monitoring and retraining loops.

• Mentor and inspire teammates, fostering a collaborative, experimentation-driven environment where cutting-edge research meets production excellence and every engineer is empowered to push AI boundaries at Airbnb.

Your Expertise:

• 5+ years of industry experience in applied AI/ML, inclusive MS or PhD in relevant fields.

• Strong programming (Python/Java) and data engineering skills.

• Proven mastery of modern AI/LLM workflows , prompt engineering, fine-tuning (LoRA, RLHF), hallucination mitigation, safety guardrails, and rigorous online/offline testing to minimize training/inference drift and ensure reliable outcomes.

• Hands-on experience with at least three of the following: PyTorch/TensorFlow, scalable inference stacks, vector search, orchestration/MLOps platforms (Kubeflow, Airflow), large-scale data streaming & processing (Spark, Ray, Kafka).

• Demonstrated success designing, deploying, and monitoring production AI systems , e.g., personalization engines, generative content services , complete with drift/cost/latency monitoring, automated retraining triggers, and cross-functional collaboration that translates ambiguous business needs into measurable AI impact.

• Prior knowledge of AI/ML applications in the Payments domain is highly desirable.

Our Commitment To Inclusion & Belonging:

Airbnb is committed to working with the broadest talent pool possible. We believe diverse ideas foster innovation and engagement, and allow us to attract creatively led people, and to develop the best products, services, and solutions.

How We'll Take Care of You:

Our job titles may span more than one career level. The actual base pay is dependent upon many factors, such as: training, transferable skills, work experience, business needs, and market demands. The base pay range is subject to change and may be modified in the future. This role may also be eligible for bonus, equity, benefits, and Employee Travel Credits.

Pay Range: $191,000-$223,000 USD

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We are looking for an Engineering Manager to join our Platform org to lead and grow teams of software engineers working on foundational platform capabilities.

You'll be responsible for defining and executing the creation of shared product capabilities at the core of Anthropic's product surfaces, while maintaining clear direction and stability for your team.

You'll partner closely with product managers, engineering leadership, talented engineers and research teams to transform emerging AI capabilities into platform capabilities.

Success in this role requires a strong ability to understand stakeholder needs, identify opportunities to share capabilities across products, understand our product and roadmap deeply, and the ability to facilitate rapid iterations to improve our product suite.

Responsibilities

• Lead and coach a high-performing team of software engineers through the complexities of 0-1 platform development
• Partner effectively with engineering and product leaders to align on direction and execution
• Create a balanced environment that encourages both iterative improvement and rigorous evaluation
• Provide clear, actionable feedback and support for engineer growth and development
• Help partner teams develop approaches for sharing capabilities and partnering to evolve our platform alongside the sophistication of our products and users
• Drive adoption of platform capabilities and learnings to inform company-wide product strategy and planning
• Represent the platform perspective and roadmap in discussions with research, product, and leadership stakeholders

You may be a good fit if you have:

• Have 3+ years of engineering management experience leading high-performing teams in ambiguous, early-stage environments
• Excel at creating psychological safety and helping teams navigate uncertainty
• Demonstrate strong interpersonal skills and ability to guide teams through rapidly evolving organization priorities while building underlying stable platforms
• Have excellent cross-functional leadership skills to build alignment between research, engineering and product
• Are skilled at facilitating decision-making rather than imposing solutions
• Have expertise in mentoring and investing energy into team culture
• Have excellent communication skills to represent the importance of and need to invest in platform capabilities at the core of our products
• Have a comprehensive technical understanding of modern software product development processes and technical stacks. Experience of AI/ML is a bonus

Strong candidates may also have experience with:

• Building products from zero to one in a startup environment
• Expertise in modern web development stacks (React, Next.js, etc)
• Experience working on AI/ML products
• Experience with identity management, authentication systems, and enterprise security standards

Logistics

Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

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Key responsibilities include:

• Leading teams across autonomy, integration, and testing by aligning technical efforts, resolving cross-functional challenges, and driving mission-focused execution.
• Integrating autonomy software onto unmanned aircraft systems, ensuring seamless operation across onboard compute, sensors, and control interfaces.
• Owning the build, configuration, and validation process for flight-ready systems; coordinating hardware/software compatibility and mission readiness.
• Traveling to test sites and supporting live flight operations, including safety checks, system bring-up, and troubleshooting under time-critical constraints.
• Diagnosing and resolving integration issues across complex autonomy software stacks and embedded systems in lab and field environments.
• Managing data collection during missions and post-test analysis, working with autonomy engineers to refine behaviors and identify improvements.
• Collaborating with autonomy, GNC, systems, and test teams to ensure mission-critical functionality is delivered on time and validated thoroughly.

Required qualifications include:

• BS/MS in Computer Science, Electrical Engineering, Mechanical Engineering, Aerospace Engineering, and/or similar degree, or equivalent practical experience.
• Typically requires a minimum of 10 years of related experience with a Bachelor’s degree; or 9 years and a Master’s degree; or 7 years with a PhD; or equivalent work experience.
• 7+ years of experience in Unmanned Systems programs in the DoD or applied R&D.
• 2+ years of people leadership experience.
• Proficiency in programming languages such as C++ and Python, and familiarity with real-time operating systems (RTOS).
• Proficiency in Linux-based development and experience working with embedded systems, shell scripting, and system diagnostics.
• Knowledge of sensor integration, sensor fusion, and middleware frameworks (e.g., ROS, DDS).
• Hands-on experience supporting flight demos or live exercises.
• Experience with simulation tools and environments (e.g., AFSIM, NGTS) for testing and validation.
• Strong problem-solving skills, with the ability to troubleshoot and optimize system performance.
• Excellent communication and teamwork skills, with the ability to work effectively in a collaborative, multidisciplinary environment.
• Ability to obtain a SECRET clearance.

Preferred qualifications include:

• Direct experience supporting unmanned aerial systems or similar flight test campaigns.
• Familiarity with autonomy stacks, flight control systems, or GNC pipelines.
• Competence in sensor integration, electronics debugging, or avionics bring-up.
• Proficiency in developing automation tools for system testing, logging, and data parsing.
• Comfortable interfacing with DoD stakeholders during field events or technical reviews.
• Experience with UCI and OMS Standards.

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Shield AI is committed to developing cutting-edge autonomy for unmanned aircraft operating across all Department of Defense (DoD) domains, including air, sea, and land. Our Flight Integration Engineers are essential to bridging the gap between R&D and deployment, ensuring that autonomous systems function reliably and effectively when and where they are needed most.

Responsibilities:

• System Integration & Deployment , Integrate autonomy software onto unmanned aircraft systems, ensuring seamless operation across onboard compute, sensors, and control interfaces.

• Pre-flight Preparation , Own the build, configuration, and validation process for flight-ready systems; coordinate hardware/software compatibility and mission readiness.

• On-site Flight Test Support , Travel to test sites and support live flight operations, including safety checks, system bring-up, and troubleshooting under time-critical constraints.

• Hardware/Software Debugging , Diagnose and resolve integration issues across complex autonomy software stacks and embedded systems in lab and field environments.

• Flight Data Capture & Analysis , Manage data collection during missions and post-test analysis, working with autonomy engineers to refine behaviours and identify improvements.

• Collaboration Across Teams , Work closely with autonomy, GNC, systems, and test teams to ensure mission-critical functionality is delivered on time and validated thoroughly.

• Continuous Improvement , Build tools and processes to improve integration timelines, flight test reliability, and team efficiency across deployment cycles.

• Support Certification and Compliance , Assist with documentation and system-level validation required for certification, airworthiness, and compliance in defense-relevant environments.

• Travel Requirement– Members of this team typically travel around 30-40% of the year (to different office locations, customer sites, and flight integration events).

Requirements:

• BS/MS in Computer Science, Electrical Engineering, Mechanical Engineering, Aerospace Engineering, and/or similar degree, or equivalent practical experience

• Typically requires a minimum of 7 years of related experience with a Bachelor’s degree; or 5 years and a Master’s degree; or 4 years with a PhD; or equivalent work experience

• Proficiency in programming languages such as C++ and Python, and familiarity with real-time operating systems (RTOS)

• Proficiency in Linux-based development and experience working with embedded systems, shell scripting, and system diagnostics

• Knowledge of sensor integration, sensor fusion, and middleware frameworks (e.g., ROS, DDS)

• Hands-on experience supporting flight demos or live exercises

• Experience with simulation tools and environments (e.g., AFSIM, NGTS) for testing and validation

• Strong problem-solving skills, with the ability to troubleshoot and optimize system performance

• Excellent communication and teamwork skills, with the ability to work effectively in a collaborative, multidisciplinary environment

• Ability to obtain a SECRET clearance

Preferred Qualifications:

• Direct experience supporting unmanned aerial systems or similar flight test campaigns

• Familiarity with autonomy stacks, flight control systems, or GNC pipelines

• Competence in sensor integration, electronics debugging, or avionics bring-up

• Proficiency in developing automation tools for system testing, logging, and data parsing

• Comfortable interfacing with DoD stakeholders during field events or technical reviews

• Experience with UCI and OMS Standards

$182,720 - $274,080 a year

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The role is highly dynamic, requiring hands-on experience, strong systems thinking, and the ability to operate effectively in fast-paced, real-world test conditions.

Shield AI is committed to developing cutting-edge autonomy for unmanned aircraft operating across all Department of Defense (DoD) domains, including air, sea, and land. Our Flight Integration Engineers are essential to bridging the gap between R&D and deployment, ensuring that autonomous systems function reliably and effectively when and where they are needed most.

Responsibilities:

• System Integration & Deployment , Integrate autonomy software onto unmanned aircraft systems, ensuring seamless operation across onboard compute, sensors, and control interfaces.

• Pre-flight Preparation , Own the build, configuration, and validation process for flight-ready systems; coordinate hardware/software compatibility and mission readiness.

• On-site Flight Test Support , Travel to test sites and support live flight operations, including safety checks, system bring-up, and troubleshooting under time-critical constraints.

• Hardware/Software Debugging , Diagnose and resolve integration issues across complex autonomy software stacks and embedded systems in lab and field environments.

• Flight Data Capture & Analysis , Manage data collection during missions and post-test analysis, working with autonomy engineers to refine behaviors and identify improvements.

• Collaboration Across Teams , Work closely with autonomy, GNC, systems, and test teams to ensure mission-critical functionality is delivered on time and validated thoroughly.

• Continuous Improvement , Build tools and processes to improve integration timelines, flight test reliability, and team efficiency across deployment cycles.

• Support Certification and Compliance , Assist with documentation and system-level validation required for certification, airworthiness, and compliance in defense-relevant environments.

• Travel Requirement , Members of this team typically travel around 30-40% of the year (to different office locations, customer sites, and flight integration events).

Requirements:

• BS/MS in Computer Science, Electrical Engineering, Mechanical Engineering, Aerospace Engineering, and/or similar degree, or equivalent practical experience

• Typically requires a minimum of 5 years of related experience with a Bachelor’s degree; or 4 years and a Master’s degree; or 2 years with a PhD; or equivalent work experience

• Proficiency in programming languages such as C++ and Python, and familiarity with real-time operating systems (RTOS)

• Proficiency in Linux-based development and experience working with embedded systems, shell scripting, and system diagnostics

• Knowledge of sensor integration, sensor fusion, and middleware frameworks (e.g., ROS, DDS)

• Hands-on experience supporting flight demos or live exercises

• Experience with simulation tools and environments (e.g., AFSIM, NGTS) for testing and validation

• Strong problem-solving skills, with the ability to troubleshoot and optimize system performance

• Excellent communication and teamwork skills, with the ability to work effectively in a collaborative, multidisciplinary environment

• Ability to obtain a SECRET clearance

Preferred Qualifications:

• Direct experience supporting unmanned aerial systems or similar flight test campaigns

• Familiarity with autonomy stacks, flight control systems, or GNC pipelines

• Competence in sensor integration, electronics debugging, or avionics bring-up

• Proficiency in developing automation tools for system testing, logging, and data parsing

• Comfortable interfacing with DoD stakeholders during field events or technical reviews

• Experience with UCI and OMS Standards

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Shield AI is committed to developing cutting-edge autonomy for unmanned aircraft operating across all Department of Defense (DoD) domains, including air, sea, and land. Our Flight Integration Engineers are essential to bridging the gap between R&D and deployment, ensuring that autonomous systems function reliably and effectively when and where they are needed most.

Responsibilities:

• System Integration & Deployment , Integrate autonomy software onto unmanned aircraft systems, ensuring seamless operation across onboard compute, sensors, and control interfaces.
• Pre-flight Preparation , Own the build, configuration, and validation process for flight-ready systems; coordinate hardware/software compatibility and mission readiness.
• On-site Flight Test Support , Travel to test sites and support live flight operations, including safety checks, system bring-up, and troubleshooting under time-critical constraints.
• Hardware/Software Debugging , Diagnose and resolve integration issues across complex autonomy software stacks and embedded systems in lab and field environments.
• Flight Data Capture & Analysis , Manage data collection during missions and post-test analysis, working with autonomy engineers to refine behaviors and identify improvements.
• Collaboration Across Teams , Work closely with autonomy, GNC, systems, and test teams to ensure mission-critical functionality is delivered on time and validated thoroughly.
• Continuous Improvement , Build tools and processes to improve integration timelines, flight test reliability, and team efficiency across deployment cycles.
• Support Certification and Compliance , Assist with documentation and system-level validation required for certification, airworthiness, and compliance in defense-relevant environments.
• Travel Requirement , Members of this team typically travel around 30-40% of the year (to different office locations, customer sites, and flight integration events).

Requirements:

• BS/MS in Computer Science, Electrical Engineering, Mechanical Engineering, Aerospace Engineering, and/or similar degree, or equivalent practical experience
• Typically requires a minimum of 10 years of related experience with a Bachelor’s degree; or 9 years and a Master’s degree; or 7 years with a PhD; or equivalent work experience
• Proficiency in programming languages such as C++ and Python, and familiarity with real-time operating systems (RTOS)
• Proficiency in Linux-based development and experience working with embedded systems, shell scripting, and system diagnostics
• Knowledge of sensor integration, sensor fusion, and middleware frameworks (e.g., ROS, DDS)
• Hands-on experience supporting flight demos or live exercises
• Experience with simulation tools and environments (e.g., AFSIM, NGTS) for testing and validation
• Strong problem-solving skills, with the ability to troubleshoot and optimize system performance
• Excellent communication and teamwork skills, with the ability to work effectively in a collaborative, multidisciplinary environment
• Ability to obtain a SECRET clearance

Preferences:

• Direct experience supporting unmanned aerial systems or similar flight test campaigns
• Familiarity with autonomy stacks, flight control systems, or GNC pipelines
• Competence in sensor integration, electronics debugging, or avionics bring-up
• Proficiency in developing automation tools for system testing, logging, and data parsing
• Comfortable interfacing with DoD stakeholders during field events or technical reviews
• Experience with UCI and OMS Standards

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At Mistral AI, we believe in the power of AI to simplify tasks, save time, and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life.

We are looking for a skilled and motivated Web Crawling Engineer to join our dynamic engineering team. The ideal candidate should have a solid background in distributed web crawling, scraping and data extraction, with experience using advanced tools and technologies to collect and process large-scale data from diverse web sources at large scale.

Responsibilities

As a Web crawling engineer, you will be responsible for:

• Developing and maintaining web crawlers using Go to extract data from target websites.
• Utilizing headless browsing techniques, such as Chrome DevTools, to automate and optimize data collection processes.
• Collaborating with cross-functional teams to identify, scrape, and integrate data from APIs and web pages to support business objectives.
• Creating and implementing efficient parsing patterns using tokenizers, regular expressions, XPaths, and CSS selectors to ensure accurate data extraction.
• Designing and managing distributed job queues using technologies such as Redis, Aerospike and Kubernetes to handle large-scale distributed crawling and processing tasks.
• Developing strategies to monitor and ensure data quality, accuracy, and integrity throughout the crawling and indexing process.
• Continuously improving and optimizing existing web crawling infrastructure to maximize efficiency and adapt to new challenges.

About You

Core programming and web technologies

• Proficiency in Go (Golang)/Rust/Zig for building scalable and efficient web crawlers.
• Deep understanding of TCP, UDP, TLS and HTTP/1.1,2,3 protocols and web communication.
• Knowledge of HTML, CSS, and JavaScript for parsing and navigating web content.
• Familiarity with cloud platforms (AWS, GCP), orchestration (Kubernetes, Nomad), and containerization (Docker) for deployment.

Data Structures & Algorithms

• Mastery of queues, stacks, hash maps, and other data structures for efficient data handling.
• Ability to design and optimize algorithms for large-scale web crawling.

Web Scraping & Data Acquisition

• Hands-on experience with networking and web scraping libraries.
• Understanding of how search engines work and best practices for web crawling optimization.

Databases & Data Storage

• Experience with SQL and/or NoSQL databases (knowing Aerospike is a bonus) for storing and managing crawled data.
• Familiarity with data warehousing and scalable storage solutions.

Distributed Systems & Big Data

• Knowledge of distributed systems (e.g., Hadoop, Spark) for processing large datasets.

Bonus Skills (Nice-to-Have)

• Experience with web archiving projects & tooling, open-source archiving is a big plus!
• Experience applying Machine Learning to improve crawling efficiency or accuracy.
• Experience with low-level networking programming and/or userspace TCP/IP stacks.

Hiring Process

Here is what you should expect:

• Introduction call - 35 min
• Hiring Manager Interview - 30 min
• Live-coding Interview - 45 min
• System Design Interview - 45 min
• Deep dive interview (optional) - 60min
• Culture-fit discussion - 30 min
• Reference checks

Additional Information

Location & Remote

This role is primarily based in one of our European offices , Paris, France and London, UK. We will prioritize candidates who either reside there or are open to relocating. We strongly believe in the value of in-person collaboration to foster strong relationships and seamless communication within our team. In certain specific situations, we will also consider remote candidates based in one of the countries listed in this job posting , currently France, UK, Germany, Belgium, Netherlands, Spain and Italy. In any case, we ask all new hires to visit our Paris HQ office:

• for the first week of their onboarding (accommodation and travelling covered)
• then at least 2 days per month

What we offer

💰 Competitive salary and equity

🧑‍⚕️ Health insurance

🚴 Transportation allowance

🥎 Sport allowance

🥕 Meal vouchers

💰 Private pension plan

🍼 Parental : Generous parental leave policy

🌎 Visa sponsorship

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Key responsibilities include:

• Leading and growing the team: Manage the SOC team, shape the roadmap, delegate effectively, and mentor engineers.

• Driving operations: Define vulnerability management processes and coordinate stakeholders for timely remediation. Design, implement, and operate SIEM/SOAR infrastructure (ingestion, normalization, correlation, alerting, playbooks). Specify logging requirements across our main stacks and centralize telemetry in the SIEM. Develop and tune correlation rules and detections; manage CTI intake and operationalize intel. Run continuous improvement to reduce false positives and raise signal quality. Establish crisp procedures for alert triage, escalation, and incident handling & investigation. Lead incident communications with stakeholders and ensure thorough documentation.

• Engineering and enablement: Contribute to security tooling, automation, and integrations that speed up detection/response. Produce guidance and documentation for product/infra teams; contribute to compliance in the SOC perimeter.

• Exercises and assurance: Coordinate red/blue exercises, post-mortems, and targeted audits to validate coverage and resilience.

The ideal candidate will have 8+ years of experience leading SOC/CSIRT functions, with proven leadership. Hands-on experience with SIEM (e.g., Elastic Security, Sekoia, Splunk) and SOAR platforms is required. Strong experience in vulnerability management (e.g., DefectDojo, Dependency-Track) and remediation workflows is also necessary. Solid grasp of the cyber kill chain / attack lifecycle, detection engineering, and log source coverage is essential. Excellent problem-solving and communication skills are required, as well as the ability to operate in a fast-paced startup environment.

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In this role, you will report to the Head of Platforms & Infrastructure and play a central role in shaping how Mercury models, governs, and operationalizes GTM data. You’ll partner closely with Data Engineering, Data Science, Solution Architecture, Platform Engineering, etc.

Some key responsibilities include:

• Owning the definition, structure, and reliability of data originating from revenue platforms (e.g., Salesforce, GTM tools, automation systems)
• Serving as the primary decision owner for GTM-sourced tables and views used for revenue execution, forecasting inputs, lifecycle tracking, and signal-based workflows
• Designing and evolving core GTM data models across Salesforce, ETL, and analytics layers
• Partnering with Data Engineering to align GTM schemas with enterprise data models and define clear data contracts between source systems and downstream consumers
• Partnering with Data Science / Analytics to ensure revenue data is interpretable, statistically sound, and reflects how the business actually operates
• Owning clarity around data ownership boundaries, shared dependencies, and escalation paths when upstream or downstream changes impact revenue integrity
• Defining and upholding data quality, freshness, consistency, and documentation standards for revenue platforms
• Monitoring and improving pipeline reliability, performance, and scalability, proactively identifying fragile or redundant transformations
• Identifying opportunities to automate manual or error-prone data workflows and reduce operational overhead
• Acting as a data thought partner to Platforms & Infrastructure, Revenue Operations, Analytics, and Security , advising on feasibility, tradeoffs, and sequencing for data-heavy initiatives

You should have:

• 7+ years of experience in data engineering or data systems roles within SaaS or technology companies
• Deep experience designing and operating production data pipelines
• Highly proficient in SQL and experienced in data modeling
• Hands-on experience with modern data stacks (e.g., Snowflake, BigQuery, Redshift)
• Experience with ETL / ELT tooling (e.g., dbt, Airflow, Census, or similar)
• Understanding of Salesforce data models and common GTM system architectures
• Ability to translate business concepts into durable, well-structured data models
• Clear communication skills with both technical and non-technical partners

Preferred qualifications include:

• Experience supporting revenue, sales, or customer lifecycle data
• Familiarity with event-based data platforms (e.g., Data Cloud or equivalents)
• Experience working alongside platform engineering and security teams
• Exposure to data governance, access controls, and compliance considerations
• Experience mentoring or guiding other data practitioners

The total rewards package at Mercury includes base salary, equity, and benefits. Our salary and equity ranges are highly competitive within the SaaS and fintech industry and are updated regularly using the most reliable compensation survey data for our industry.

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Responsibilities:

• Own critical production services end-to-end, from design and code review through deployment, operation, and incident response
• Profile, benchmark, and rewrite hot paths to eliminate bottlenecks as Hebbia scales
• Lead incident response and drive post-mortem culture, translating findings into code changes and architectural improvements rather than runbooks
• Design and build observability frameworks from scratch, writing custom instrumentation, alerting logic, and debugging tooling that surfaces production issues before customers feel them
• Define and enforce SLOs across platform services and build the feedback loops that keep engineering teams accountable to them
• Own capacity planning and cost efficiency: model growth, right-size infrastructure, and write automation that prevents over-provisioning and resource exhaustion
• Build robust, well-tested internal platforms and deployment tooling held to the same engineering standards as customer-facing code
• Own and continuously improve CI/CD systems so engineering teams can ship safely and quickly
• Embed with product engineering teams as a peer software engineer, contributing directly to production codebases and co-designing systems for reliability from the start
• Partner on infrastructure security through threat modeling, hardening, and automated compliance tooling

Who You Are:

• 5+ years software development with a track record of writing, shipping, and maintaining production services, not just operating infrastructure
• Production-grade proficiency in at least one systems or backend language: Go, Python, C++, or Rust
• Proven experience as a Production Engineer, SRE, or software engineer with a deep infrastructure focus, comfortable owning services end-to-end across the full stack
• Deep understanding of distributed systems
• Container orchestration expertise and hands-on experience debugging complex distributed failures in production
• Working knowledge of OS-level concepts
• Cloud platform fluency (AWS preferred)
• Experience in building and maintaining observability stacks
• Strong CI/CD pipeline expertise and a track record of improving developer velocity without sacrificing safety
• Background at a company with a Production Engineering or software-focused SRE culture is a strong plus
• Experience building platforms for AI/ML workloads or high-throughput document processing pipelines is a plus

Compensation: The salary range for this role is $160,000 to $300,000. This range may be inclusive of several career levels at Hebbia and will be narrowed during the interview process based on the candidate’s experience and qualifications. Adjustments outside of this range may be considered for candidates whose qualifications significantly differ from those outlined in the job description.

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You'll sit at the intersection of engineering, product, and GTM. Your scrappy prototypes, experiments, and content will be the first touchpoint for new creators, studios, and Fortune 500 innovation teams. When you do your job well, the rest of the company feels it in tomorrow's dashboards.

Responsibilities:

• Spin up lightweight client libraries, demo apps, or event microsites in a few hours.
• Run data-driven experiments. Segment cohorts, design A/B tests, and automate reporting. We have a clear, metric-based view of acquisition cost and activation rate for every segment.
• Draft compelling blog posts, tweets, and teardown threads (zero “AI slop”).
• Our content consistently drives qualified sign-ups and sparks industry conversations.
• Own customer touchpoints: Meet prospects, debug their first calls, and represent fal at meetups and hackathons. Prospects leave every interaction saying, “These folks get it,and ship fast.”
• Identify high-leverage problems, time-box solutions, and ship. After ramp-up, you propose your own roadmap,and we mostly just say “Yes.”

Nice to have:

• Prior experience in PLG or developer-tool startups
• Familiarity with growth analytics stacks
• A portfolio of technical writing, open-source libs, or side projects

Compensation:

$170,000 - $220,000 + equity + comprehensive benefits package

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We believe in a world where homes are owned by regular people, not corporations. Our mission is to provide authentic belonging experiences, empowering residents to become homeowners and homeowners to achieve financial freedom.

The Role

Belong is seeking a Sales Floor Operations Manager to help scale a fast-growing, high-velocity B2C sales organization without sacrificing execution quality. This is a hybrid role combining Sales Floor Management and Sales Operations / Revenue Operations ownership. It’s designed for an operator who thrives in the middle of action , someone who can enforce standards, bring structure, and translate strategy into daily execution.

Responsibilities

• Own day-to-day execution on the sales floor
• Drive discipline around activity levels and progression steps, pipeline hygiene and follow-up quality, cadence and sequencing adherence
• Enforce standards such as punctuality, preparedness, and accountability
• Partner closely with Sales Leadership to ensure strategy is executed without slowing the team down
• Act as the connective layer between leadership direction and rep execution
• Own cleanliness, accuracy, and reliability of Salesforce / Foundation
• Perform daily pipeline inspections and reporting
• Serve as the Salesforce power user for the Sales organization: CRM configuration, dashboards and reporting, dialers, automation, and tooling
• Simplify, document, and continuously improve sales processes
• Translate sales strategy into operational workflows that scale
• Identify bottlenecks and proactively implement fixes
• Use AI-powered tools to improve pipeline visibility, forecasting, and rep productivity
• Identify opportunities to automate manual workflows and reduce operational friction
• Partner with Sales, Product, and Ops teams to continuously upgrade tooling and processes

What We’re Looking For

• Strong background in B2C high-volume, high-velocity sales environments
• Previous experience managing or operating a fast-paced sales floor
• Proven Salesforce power user (reporting, automation, dashboards)
• Hands-on experience with modern sales tech stacks (CRM, dialers, automation tools)
• Familiarity with AI applied to sales workflows is a strong plus

Why This Role Matters

This role is foundational to scaling sales without breaking execution. Hiring more reps only works if the system behind them is bulletproof. You’ll help design and run the operating system for a repeatable, high-performing sales org. Your work will directly impact revenue growth, forecasting accuracy, and team performance

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You will own the integration of complex subsystems, ensuring the robustness, scalability, and maintainability of simulation platforms. You will act as the technical point of contact for issue resolution, applying strong engineering rigor and clear communication with stakeholders.

You will develop, integrate, and validate SoC peripheral models using SystemC/TLM across multiple application domains, authoring and reviewing ESL model specifications and interface contracts. You will lead software bring-up activities for Linux, Android, AUTOSAR, and embedded stacks on virtual prototypes, debugging boot flows, drivers, and peripheral interactions.

You will support customer engagements by understanding their use cases, proposing effective solutions, and driving timely and transparent resolutions to challenges. You will mentor junior engineers and consultants, lead design/code/test reviews, and proactively manage risks and priorities across multiple workstreams.

You will enable customers to accelerate software development and validation cycles by providing high-fidelity virtual prototypes ahead of silicon availability. You will drive innovation in virtual platform modelling, influencing industry standards and best practices across multiple technology domains.

You will enhance the scalability and maintainability of Synopsys' SystemC/TLM simulation platforms, supporting rapid evolution and new feature adoption. You will empower global engineering teams through mentorship and technical leadership, raising the overall bar for quality and execution excellence.

You will contribute directly to customer success by resolving complex technical challenges and delivering robust, production-grade solutions. You will shape the product roadmap and technical direction by identifying emerging needs and proposing forward-thinking solutions for future platforms.

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As a Backend Engineer, you will help us exemplify, measure and raise the reliability of data infrastructure of squads across different verticals within Spotify. You'll work closely with engineers to provide OLAP capabilities to build dynamic, reliable data visualizations and share responsibility with them in diagnosing, resolving, and preventing production issues.

Key responsibilities include:

• Building, operating, and evolving data analytics platforms that include backend services as well as OLAP data stores (Druid) for teams building analytics across Spotify.
• Building internal tooling, libraries, and services that streamline integration patterns with our analytics platform.
• Advocating for best practices in service design, data modeling, schema evolution, and contract testing to ensure long-term maintainability.
• Working in an autonomous, multi-functional environment and collaborating with squads across Spotify to continuously iterate and deliver on new product objectives.

To succeed in this role, you will need:

• 3+ years of relevant experience with distributed datastores and backend services.
• Proficiency in Java and a willingness to learn Kubernetes and Terraform.
• Understanding of data modeling, dimensional schemas, and analytical query patterns.
• Experience building internal developer tools, libraries, or shared services that support large engineering organisations.
• A strong sense of ownership of service quality, SLOs, and operational excellence.
• Familiarity with OLAP databases or analytics warehouses (e.g., Druid, ClickHouse, Pinot, BigQuery, Snowflake).
• Comfort with metrics-driven development and observability stacks (Prometheus, Grafana, similar).
• Excellent communication and interpersonal skills, with the ability to work effectively with cross-functional teams.

In return, we offer a competitive salary range of $125,562-$179,374, plus equity, as well as a comprehensive benefits package including health insurance, six months' paid parental leave, 401(k) retirement plan, monthly meal allowance, 23 paid days off, 13 paid flexible holidays, and paid sick leave.

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Founded by British makeup artist and beauty entrepreneur Charlotte Tilbury MBE in 2013, Charlotte Tilbury Beauty has revolutionised the face of the global beauty industry.

The AI & ML Engineering team accelerates the adoption of AI across the business, championing innovation while ensuring our machine learning products are robust, scalable, and cost-efficient.

Responsibilities:

Partner with stakeholders to scope problems and identify the right solution - whether leveraging existing AI tools or building custom workflows & solutions.

Design and implement agentic systems using techniques spanning RAG, grounding, prompt engineering, and orchestration on a GCP-first stack.

Build and maintain production ML pipelines and services for non-GenAI use cases (e.g. recommender systems, customer segmentation models, marketing optimisation modules, leveraging supervised, unsupervised and/or econometric modelling approaches).

Develop APIs and microservices for AI/ML solutions, ensuring security, scalability, and observability.

Implement CI/CD for ML services, writing infrastructure as code, and monitoring for model/data drift and performance.

Establish robust guardrails for safe AI usage, including prompt security, practical evaluation frameworks, and compliance with privacy regulations.

Drive and evangelize best practices, reusable templates, and documentation to scale AI/ML delivery across the business.

Collaborate with data engineers, data scientists, front & back-end engineers, product managers, legal & infosec colleagues to deliver impactful solutions end-to-end.

Who you will work with

The AI & ML Engineer Lead and the wider data team.

About you

The role requires a blend of technical depth and product sense, including:

Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.

Strong Python engineering skills (FastAPI, testing, typing) and experience with cloud-native development (GCP preferred).

Hands-on experience with GCP Vertex AI (model endpoints, pipelines, embeddings, vector search) or equivalent cloud-native ML platforms (e.g. AWS SageMaker, Azure ML) and agent orchestration frameworks such as LangChain and LangGraph.

Solid understanding of MLOps - CI/CD, IaC (Terraform), experiment tracking, model registry, and monitoring.

Proven experience deploying and operating ML systems in production (batch and real-time).

Familiarity with RAG architectures, prompt engineering, and evaluation techniques.

Strong grasp of security, privacy, and governance principles (IAM, secrets, PII handling).

Excellent communication skills and ability to work with non-technical stakeholders.

In addition to the above, we would LOVE if you have:

Experience with vector databases and retrieval strategies.

Knowledge of recommender systems and ranking models.

Familiarity with LLM evaluation tools (e.g., RAGAS, TruLens, LangSmith, Arize).

Exposure to feature stores, data lineage, and observability stacks.

Experience in e-commerce or retail environments.

Demonstrable ability to weigh up build/build/configure decisions in the LLM space.

Why join us?

Be a part of this values driven, high growth, magical journey with an ultimate vision to empower everyone, everywhere to be the best version of themselves.

We’re a hybrid model with flexibility, allowing you to work how best suits you.

25 days holiday (plus bank holidays) with an additional day to celebrate your birthday.

Inclusive parental leave policy that supports all parents and carers throughout their parenting and caring journey.

Financial security and planning with our pension and life assurance for all.

Wellness and social benefits including Medicash, Employee Assist Programs and regular social connects with colleagues.

Bring your furry friend to work with you on our allocated dog friendly days and spaces.

And not to forget our generous product discount and gifting!

At Charlotte Tilbury Beauty, our mission is to empower everybody in the world to be the most beautiful version of themselves.

We celebrate and support this by encouraging and hiring people with diverse backgrounds, cultures, voices, beliefs, and perspectives into our growing global workforce.

By doing so, we better serve our communities, customers, employees - and the candidates that take part in our recruitment process.

If you want to learn more about life at Charlotte Tilbury Beauty please follow our LinkedIn page!

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You will focus on process management and execution, ensuring our technical infrastructure initiatives run smoothly across global time zones while providing a structured framework for our engineering teams to succeed.

This is a high-impact Program Manager role with a strong focus on operations and program support within a mission-critical technical environment. You will be responsible for the program operations of our GenAI serving stack, bridging the gap between technical design and execution.

The role is dynamic and requires a leader who can thrive in an agile, fast-moving environment where priorities can shift quickly. You will manage critical workflows such as accelerating technical design reviews, enhancing cross-functional collaborations, and ensuring that the program's objectives are met with precision and efficiency.

Key responsibilities include defining and owning program charters, leading design reviews and technical steering discussion forums, partnering with engineers to resolve operational bottlenecks, and organizing program reviews and summits.

We are looking for a disciplined program leader who excels at bringing structure to complex environments and possesses the soft skills to influence stakeholders across different regions.

Requirements include proven experience as a Program Manager, experience working directly with engineers on large-scale infrastructure projects, and a demonstrated ability to create and implement process improvements.

Preferred qualifications include familiarity with software stacks, agile methodologies, and the AI/ML realm, specifically Gemini or similar LLM serving stacks, as well as experience working effectively with teams across multiple time zones.

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About Us

DeepMind's RL team is a long-standing and tight-knit team of collaborative scientists and engineers, led by Tom Schaul. We tackle large scale research challenges in reinforcement learning. We design, refine, and scale RL algorithms and deliver meaningful scientific or product impact. Over the past decade, members of the RL team have been instrumental in building DQN, AlphaGo, Rainbow, AlphaZero, MuZero, AlphaStar, AlphaProof and Gemini.

The Role

As a Research Scientist, you'll use machine learning knowledge and technical know-how to innovate, drive research projects, as well as apply research to impactful problems. You will be expected to implement code, run experiments, own results end-to-end, communicate them internally or externally, as well as collaborate with and empower others.

Your work may involve:

• Initiating or pursuing novel research directions, by proposing and testing research hypotheses.
• Implementing algorithm ideas and run end-to-end experiments, including setup, execution, analysis, and iteration.
• Sharing your skills and knowledge with other researchers.
• Building or improving infrastructure for research at scale.
• Designing evaluations and ablations that answer real questions and change minds.
• Analyzing results carefully, including debugging and failure analysis.
• Communicating clearly through plots, writeups, and paper-ready narratives and figures.
• Contributing to a culture of first-principles thinking, high standards, and direct, constructive feedback.

Our projects span the full range of state-of-the-art machine learning and AI fields, including large language models, distributed machine learning techniques, and much more, but with an emphasis on reinforcement learning.

We take a holistic view of people's backgrounds, and do not expect you to be an expert in all areas. We do expect you to proactively and quickly adopt new technologies and systems, but we also invest a lot of time in training and helping people to continually learn as part of their role.

About You

In order to set you up for success as a Research Scientist at Google DeepMind, we look for the following skills and experience:

• A passion for reinforcement learning
• A research track record in RL, including peer-reviewed publications.
• Strong implementation ability and comfort working in research codebases.
• Evidence of owning experiments end-to-end, including analysis and interpretation.
• Strong communication skills and a bias toward clarity and honesty regarding results.
• High agency and drive: You push projects forward, prioritize effectively, and take initiative.
• PhD in ML preferred, or equivalent practical experience.

In addition, the following would be an advantage:

• Experience with RL for sequence models, post-training, preference-based learning, or agentic systems.
• Experience with modern research stacks (e.g., JAX/Flax or PyTorch) and scaling experiments.
• Strong experimental taste: Good judgment regarding baselines, ablations, and what is worth testing.
• Comfort with scaling, evaluation methodologies, and diagnosing complex failure modes.
• A focus on craft: You care about doing excellent work while maintaining a high velocity.

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We are looking for a SOC (Security Operations Center) Team Lead to build and lead our SOC function end-to-end. You will own vulnerability management, alerting and detection engineering, incident response, and the security tooling/infrastructure that enable these missions. You’ll define processes, collaborate closely with Product, Infra and IT, and continuously improve detection quality and response time.

Key responsibilities

• Lead & grow the team: Manage the SOC team, shape the roadmap, delegate effectively, and mentor engineers.

• Drive operations: - Define vulnerability management processes and coordinate stakeholders for timely remediation. - Design, implement, and operate SIEM/SOAR infrastructure (ingestion, normalization, correlation, alerting, playbooks). - Specify logging requirements across our main stacks and centralize telemetry in the SIEM. - Develop and tune correlation rules and detections; manage CTI intake and operationalize intel. - Run continuous improvement to reduce false positives and raise signal quality. - Establish crisp procedures for alert triage, escalation, and incident handling & investigation. - Lead incident communications with stakeholders and ensure thorough documentation.

• Engineering & enablement: - Contribute to security tooling, automation, and integrations that speed up detection/response. - Produce guidance and documentation for product/infra teams; contribute to compliance in the SOC perimeter.

• Exercises & assurance: - Coordinate red/blue exercises, post-mortems, and targeted audits to validate coverage and resilience.

Requirements

• 8+ years of experience leading SOC/CSIRT functions, with proven leadership.

• Hands-on with SIEM (e.g., Elastic Security, Sekoia, Splunk) and SOAR platforms.

• Strong experience in vulnerability management (e.g., DefectDojo, Dependency-Track) and remediation workflows.

• Solid grasp of the cyber kill chain / attack lifecycle, detection engineering, and log source coverage.

• Excellent problem-solving and communication skills; able to operate in a fast-paced startup environment.

• Builder mindset: pragmatic, automation-oriented, comfortable with ambiguity and ownership.

Nice to have

• Bring scripting/automation skills (e.g., Python, Bash) for data pipelines/playbooks.

• Know modern infra/app stacks (Linux, containers, Kubernetes, cloud), EDR/IDS/IPS.

• Have exposure to compliance frameworks (ISO 27001, SOC 2) and security audits/pen-tests.

• Have run purple team exercises and measurable detection-coverage programs.

• Are comfortable partnering with Product/Platform teams and influencing roadmaps.

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At Mistral AI, we believe in the power of AI to simplify tasks, save time, and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life.

We are a global company with teams distributed between France, USA, UK, Germany and Singapore. We are a diverse workforce that thrives in competitive environments and is committed to driving innovation.

Why This Role Matters

You will be the technical linchpin between Mistral and our strategic partners in ASEAN (Nvidia, Dell, Hyperscalers, Global System Integrators), translating our open-weight models and sovereign AI architecture into deployable, scalable solutions.

By designing joint architectures, influencing partner GTM motions, and earning a seat at the CIO/CTO table, you will accelerate Mistral’s technical credibility and deployment velocity across Asia Pacific.

This is a foundational role where you will define how open-weight AI is operationalized at scale in the region.

What You Will Do

Partner Technical Leadership & Architecture Design

• Lead the technical design, deployment, and enablement of Mistral’s partner solutions, bridging our AI models with partner infrastructure (Nvidia, Dell, Hyperscalers, GSIs) to deliver scalable AI Labs, AI Factories, and sovereign AI architectures.

• Serve as the trusted technical advisor to partner CTOs, CIOs, and engineering leaders—shaping joint architectures, guiding GPU/model deployment strategies, and accelerating GTM execution.

• Design reference architectures and deployment patterns for partner-led implementations (e.g., multi-GPU inference clusters, AI Lab topologies, private AI clouds).

• Innovate the Executive Briefing Center (EBC) function for technical leaders (CIOs, CTOs, CDOs), positioning Mistral as the default choice for enterprise AI.

• Co-design sovereign AI reference architectures with Nvidia and Dell (H100, H200, GB200 platforms).

Co-Sell & Revenue Enablement

• Collaborate with Mistral’s partner and sales teams to progress deals, providing technical expertise to penetrate accounts and influence GTM pipeline.

• Support partners in qualifying/disqualifying opportunities, ensuring Mistral solutions unlock maximum value for customers.

• Deploy Mistral’s enterprise AI suite (models, fine-tuning, use-case building) in partner-led environments, tailoring solutions to customer requirements.

Trusted Advisor & Lighthouse Implementations

• Drive strategic partner-led opportunities through technical discovery, architecture design, and POC execution.

• Lead lighthouse deployments that become referenceable case studies (e.g., Singtel AI Grid, Accenture AI Lab).

• Establish a scalable partner enablement framework, training 100+ partner engineers across ASEAN.

Product Feedback & Internal Collaboration

• Coordinate with Mistral’s product and engineering teams to relay partner-specific requirements and feedback.

• Align joint GTM and technical execution between Mistral Science, Partner Engineering, and partner field teams.

About You

Must-Have

• 10–15 years’ experience in partner-facing technical sales or solution architecture (e.g., Partner SA, Alliance Architect, Partner Technology Strategist).

• Proven ability to engage C-suite and senior technical stakeholders (CTO, CIO, Chief Architect) in strategic architecture discussions.

• Deep GenAI/LLM expertise: RAG, fine-tuning, prompt engineering, model evaluation, and deployment patterns.

• Technical mastery of AI/ML infrastructure (GPU clusters, cloud platforms, model deployment frameworks).

• Track record of co-designing/deploying joint solutions with ecosystem partners (Nvidia, Dell, AWS, Accenture, etc.).

• Executive communication: Ability to articulate science-driven value propositions to technical and business audiences.

• Entrepreneurial mindset: Operates autonomously in high-growth environments; creates playbooks, not follows them.

• Fluent in English; confident working across diverse, cross-cultural teams in Asia.

Nice-to-Have

• Experience with open-weight LLMs or open-source AI stacks (Mistral, Hugging Face, LangChain, vLLM, RAG frameworks).

• Prior involvement in AI Lab, AI Factory, or Sovereign Cloud deployments.

• Familiarity with data governance, model evaluation, and GPU sizing for large-scale inference.

• Network across GSIs and infrastructure partners in Asia

• Exposure to multi-region partner programs or joint GTM initiatives in APJ.

• Bonus languages: Korean, Japanese, or Mandarin for regional partner engagement.

What we offer

• 💰 Competitive cash salary and equity

• 🚑 Health Insurance : Best in Class

• 🥎 Sport : $90 for gym membership allowance

• 🥕 Food : $200 monthly allowance for meals (solution might evolve as we grow bigger)

• 🚴 Transportation : $120/month for public transport or Parking charges reimbursed

• 🏝️ PTO: 18 per year

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Your period at Fifty-Five will start with a training period in web analysis, tag management, and the framework we apply to these activities. During this training, you will take on stimulating and engaging projects, preparing you for the client initiatives you will manage in your role. During these projects, you will be continuously supported and trained, enriching your experience and allowing you to contribute your knowledge to the rest of the Fifty-Five team.

Responsibilities

• Implement and manage data collection tags on websites and mobile applications
• Conduct web analytics and media monitoring
• Implement and manage marketing technology solutions
• Conduct audits and quality guarantees
• Provide technical support to internal and external stakeholders

Requirements

• Knowledge of fundamental web concepts (HTML/CSS)
• Ability to read and write JavaScript
• 2-3 years of experience with tag management tools such as Google Tag Manager, Tealium or Adobe Launch
• 2-3 years of experience in implementing and maintaining digital analytics platforms such as Google Analytics or Adobe Analytics
• Ability to create technical documentation
• Excellent analytical and problem-solving skills
• Organisational and project management skills (organisation of meetings, management of deadlines and relationships with clients)
• Ability to communicate and translate technical issues into simple language
• Ability to work with external and internal multifunctional teams
• Excellent written and oral communication skills
• Ability to work in a dynamic environment
• Fluency in Italian and English

Preferred

• Experience with multiple web analytics tools
• Experience with multiple tag management systems
• Experience with app analytics deployment
• Knowledge of marketing technology stacks (ideal Google Marketing Platform)

Benefits

• Smart working policy
• Particular attention to work-life balance in respect of the right to disconnection
• Multicultural environment with colleagues from over 20 different nationalities
• Internal values focused on excellence, benevolence and sharing
• Continuous training (and recognised) on the ecosystem, digital technologies and soft skills (e.g. public speaking, team management)
• Opportunity to participate in internal projects such as Data Hive (a 'tech for good' project promoted by Fifty-Five employees, whose purpose is to put their knowledge and skills at the disposal of charitable organisations), DEI@55 (a working group on diversity and inclusion within Fifty-Five and the technology sector more broadly), Sustainability@55 (a team that helps to implement sustainable practices internally and with our clients)

Fifty-Five is convinced that diversity and inclusion are real forces. We commit to ensuring equal treatment of all received applications, without distinction of gender, age, origin, sexual orientation, health status or political or religious opinion. Meet the Fifty-Five team!

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Be part of a globally renowned management consulting firm that is on the front-line of industry disruption in next-generation digital services and consulting.

The Team

Good work is based on curiosity, openness, and transparency. This guides the way we work and behave. Our goal is to create purposeful work we can identify with: We strive to imagine products and services that add value to people’s lives, things people actually want and welcome.

Our digital teams bring multidisciplinary creative thinking, digital strategy and technology thought leadership to every stage of the engagement. By combining strategy, technology, data science, and creative design expertise with an inventive and open mindset, we partner with our clients to innovate and transform – and identify next business opportunities.

We are always learning, and we encourage and enable personal development, intellectual growth, teaching and coaching. We empower our people to take ownership and be accountable for – and beyond client work.

The Role

As a SAFE AGILE Expert, you will be accountable for ensuring new and existing teams are enabled to deliver business impact by establishing SAFE AGILE regimes and introducing sustainable agile behaviours. You will achieve this through coaching, constructive challenge and sharing personal experiences with our clients and your teams.

Beyond delivery ownership, you are serving as trusted advisor, facilitator, coach, and trainer: You will coach inclusively, encouraging creativity and problem-solving techniques, building and maintaining strong partnerships with our clients.

About You

• You are an expert in SAFE AGILE and/or Scrum, Scale, SAFE, LeSS and related methodologies who has successfully implemented SAFE AGILE regimes in different cultures and environments, supporting teams of varying size and complexity. Accompanying certifications as an Agile Coach, Scrum Master certification (CSM, PSM), Product Owner, or Release Train Engineer are nice-to-have
• You have demonstratable experience in implementing large scale digital solutions and platforms in multi-vendor environments
• You are comfortable challenging and advising our clients, in a way that encourages them to improve and embed new ways of working
• You have a good understanding of customer interaction technology stacks such as Salesforce, Adobe and SAP Hybris and their re-usability principles
• You offer excellent training, moderation, and facilitation skills
• You have strong written and verbal communication skills in German and English

Benefits

• Industry-leading compensation and benefits
• Top training and development opportunities
• Curious to learn more? We’d love to hear from you.... Join us today!

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At BlackRock, technology is the foundation of our business. As a DevOps Engineer, Associate, you will lead the reliability, automation, and production stability of mission-critical enterprise-scale software.

This role is ideal for engineers who like to innovate and solve complex challenges while fostering a culture of excellence and continuous improvement.

About Post Trade Accounting (PTA)

PTA is a major strategic area within Aladdin and one of BlackRock's largest engineering investments. It is responsible for the systems that ensure accurate, scalable, and efficient accounting across global operations. PTA is expanding into data analytics and pipeline initiatives using Snowflake, Redis, and Kafka to manage high-volume, real-time data.

Key Responsibilities

• Implement and refine dashboards, monitoring, alerting, and observability using Prometheus, Grafana, Splunk, and OpenTelemetry.
• Ensure production readiness through capacity planning, change reviews, and disaster-recovery exercises.
• Drive long-term remediation by translating operational learnings into engineering backlog priorities.
• Influence service design toward operability, observability, and supportability.
• Work closely with L1/L2/L3 support teams to define escalation paths, SLAs, and handover processes.
• Design and promote agentic automation solutions to reduce repetitive manual tasks across DevOps and Application Support workflows.
• Champion a shift from reactive support toward proactive, intelligent operations.
• Bridge gaps between Engineering and Operations through shared technical context.

Qualifications / Competencies

• B.S./M.S. in Computer Science, Engineering, or related discipline.
• 3+ years of professional experience across DevOps, SRE, Product Engineering and/or Production Support roles.
• Strong knowledge of Java and Spring-based services, and enterprise integration patterns.
• Strong hand-on experience with observability and monitoring stacks.
• Exposure to AI-assisted tooling for operations, automation, or observability.
• Solid understanding of distributed systems and event-driven architectures.
• Excellent communication skills and ability to influence engineering and operations teams.
• Experience with Sybase, SQL Server, Snowflake, Cassandra, Redis, and Kafka is a plus.

Nice to Have

• Experience with service resiliency patterns or multiregion deployments
• Experience with Kubernetes, Docker, or cloud-native environments (AWS/GCP).
• Familiarity with financial systems, accounting, or investment technology.

Our benefits

To help you stay energized, engaged and inspired, we offer a wide range of employee benefits including: retirement investment and tools designed to help you in building a sound financial future; access to education reimbursement; comprehensive resources to support your physical health and emotional well-being; family support programs; and Flexible Time Off (FTO) so you can relax, recharge and be there for the people you care about.

Our hybrid work model

BlackRock's hybrid work model is designed to enable a culture of collaboration and apprenticeship that enriches the experience of our employees, while supporting flexibility for all. Employees are currently required to work at least 4 days in the office per week, with the flexibility to work from home 1 day a week. Some business groups may require more time in the office due to their roles and responsibilities.

About BlackRock

At BlackRock, we are all connected by one mission: to help more and more people experience financial well-being. Our clients, and the people they serve, are saving for retirement, paying for their children's educations, buying homes and starting businesses. Their investments also help to strengthen the global economy: support businesses small and large; finance infrastructure projects that connect and power cities; and facilitate innovations that drive progress.

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About the Team

We build foundational AI infrastructure that enables large-scale training and inference across diverse workloads and rapidly evolving hardware generations. Our work directly shapes how AI systems are designed, deployed, and scaled today and into the future. Engineers on this team operate with end-to-end ownership, deep technical rigor, and a strong bias toward real-world impact.

Microsoft Superintelligence Team

Microsoft Superintelligence team’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

This role is part of Microsoft AI’s Superintelligence Team. The MAIST is a startup-like team inside Microsoft AI, created to push the boundaries of AI toward Humanist Superintelligence—ultra-capable systems that remain controllable, safety-aligned, and anchored to human values. Our mission is to create AI that amplifies human potential while ensuring humanity remains firmly in control. We aim to deliver breakthroughs that benefit society—advancing science, education, and global well-being. We’re also fortunate to partner with incredible product teams giving our models the chance to reach billions of users and create immense positive impact. If you’re a brilliant, highly-ambitious and low ego individual, you’ll fit right in—come and join us as we work on our next generation of models!

Responsibilities

Lead the co-design of AI systems across hardware and software boundaries, spanning accelerators, interconnects, memory systems, storage, runtimes, and distributed training/inference frameworks. Drive architectural decisions by analyzing real workloads, identifying bottlenecks across compute, communication, and data movement, and translating findings into actionable system and hardware requirements. Co-design and optimize parallelism strategies, execution models, and distributed algorithms to improve scalability, utilization, reliability, and cost efficiency of large-scale AI systems. Develop and evaluate what-if performance models to project system behavior under future workloads, model architectures, and hardware generations, providing early guidance to hardware and platform roadmaps. Partner with compiler, kernel, and runtime teams to unlock the full performance of current and next-generation accelerators, including custom kernels, scheduling strategies, and memory optimizations. Influence and guide AI hardware design at system and silicon levels, including accelerator microarchitecture, interconnect topology, memory hierarchy, and system integration trade-offs. Lead cross-functional efforts to prototype, validate, and productionize high-impact co-design ideas, working across infrastructure, hardware, and product teams. Mentor senior engineers and researchers, set technical direction, and raise the overall bar for systems rigor, performance engineering, and co-design thinking across the organization.

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We pursue this mission through deep hardware–software co-design, combining rigorous systems thinking with hands-on engineering. The team invests heavily in understanding real production workloads large-scale training, inference, and emerging multimodal models and translating those insights into concrete improvements across the stack: from kernels, runtimes, and distributed systems, all the way down to silicon-level trade-offs and datacenter-scale architectures.

This role sits at the boundary between exploration and production. You will work closely with internal infrastructure, hardware, compiler, and product teams, as well as external partners across the hardware and systems ecosystem. Our operating model emphasizes rapid ideation and prototyping, followed by disciplined execution to drive high-leverage ideas into production systems that operate at massive scale.

In addition to delivering real-world impact on large-scale AI platforms, the team actively contributes to the broader research and engineering community. Our work aligns closely with leading communities in ML systems, distributed systems, computer architecture, and high-performance computing, and we regularly publish, prototype, and open-source impactful technologies where appropriate.

Microsoft Superintelligence Team Microsoft Superintelligence team’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

This role is part of Microsoft AI’s Superintelligence Team. The MAIST is a startup-like team inside Microsoft AI, created to push the boundaries of AI toward Humanist Superintelligence—ultra-capable systems that remain controllable, safety-aligned, and anchored to human values. Our mission is to create AI that amplifies human potential while ensuring humanity remains firmly in control. We aim to deliver breakthroughs that benefit society—advancing science, education, and global well-being. We’re also fortunate to partner with incredible product teams giving our models the chance to reach billions of users and create immense positive impact.

Responsibilities Lead the co-design of AI systems across hardware and software boundaries, spanning accelerators, interconnects, memory systems, storage, runtimes, and distributed training/inference frameworks.

Drive architectural decisions by analyzing real workloads, identifying bottlenecks across compute, communication, and data movement, and translating findings into actionable system and hardware requirements.

Co-design and optimize parallelism strategies, execution models, and distributed algorithms to improve scalability, utilization, reliability, and cost efficiency of large-scale AI systems.

Develop and evaluate what-if performance models to project system behavior under future workloads, model architectures, and hardware generations, providing early guidance to hardware and platform roadmaps.

Partner with compiler, kernel, and runtime teams to unlock the full performance of current and next-generation accelerators, including custom kernels, scheduling strategies, and memory optimizations.

Influence and guide AI hardware design at system and silicon levels, including accelerator microarchitecture, interconnect topology, memory hierarchy, and system integration trade-offs.

Lead cross-functional efforts to prototype, validate, and productionize high-impact co-design ideas, working across infrastructure, hardware, and product teams.

Mentor senior engineers and researchers, set technical direction, and raise the overall bar for systems rigor, performance engineering, and co-design thinking across the organization.

Qualifications Bachelor’s Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.

Additional or Preferred Qualifications Master’s Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR Bachelor’s Degree in Computer Science or related technical field AND 12+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.

Strong background in one or more of the following areas: AI accelerator or GPU architectures Distributed systems and large-scale AI training/inference High-performance computing (HPC) and collective communications ML systems, runtimes, or compilers Performance modeling, benchmarking, and systems analysis Hardware–software co-design for AI workloads Proficiency in systems-level programming (e.g., C/C++, CUDA, Python) and performance-critical software development.

Proven ability to work across organizational boundaries and influence technical decisions involving multiple stakeholders. Experience designing or operating large-scale AI clusters for training or inference. Deep familiarity with LLMs, multimodal models, or recommendation systems, and their systems-level implications. Experience with accelerator interconnects and communication stacks (e.g., NCCL, MPI, RDMA, high-speed Ethernet or InfiniBand). Background in performance modeling and capacity planning for future hardware generations. Prior experience contributing to or leading hardware roadmaps, silicon bring-up, or platform architecture reviews. Publications, patents, or open-source contributions in systems, architecture, or ML systems are a plus.

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The Application Security team at Anthropic is at the forefront of building security into every phase of the software development lifecycle. In this hands-on technical role, you will partner closely with software engineers and researchers to ensure security is a core consideration from initial design through implementation.

You will lead threat modeling and secure design reviews to proactively identify and mitigate risks early, and help with continuous risk assessment. You will build tools and systems to support developers shipping code securely, adhering to secure coding best practices.

Your insights will shape our tooling, detection capabilities, and defenses against emerging threats to AI/ML. You'll develop the standards, processes, and educational resources that enable all Anthropic engineers to be security champions.

Responsibilities:

• Help secure AI products and internal tools that are introducing industry-novel security risks and pushing established security boundaries
• Lead “shift left” security efforts to build security into the software development lifecycle
• Conduct secure design reviews and threat modeling. Identify and prioritise risks, attack surfaces, and vulnerabilities
• Develop tooling to scale security code reviews and respond to developer questions, including advising developers on remediating vulnerabilities and following secure coding practices
• Manage Anthropic's vulnerability management program, including integrating data ingestion pipelines, coding logic to prioritise vulnerability fixes, supporting teams remediating vulnerabilities and developing automated systems at scale
• Oversee Anthropic's bug bounty program. Set scope, validate submissions, perform root cause analysis, coordinate remediation with engineering teams, and award bounties. Cultivate relationships with the ethical hacker community
• Collaborate closely with product engineers and researchers to instill security best practices. Advocate for secure architecture, design, and development
• Develop and document security policies, standards, and playbooks. Conduct security awareness training for engineers

You may be a good fit if you:

• Have 5+ years of hands-on experience in application and infrastructure security, including securing cloud-based and containerized environments
• Strong proficiency in at least one programming language (e.g., Python, Rust, Go, Java)
• Lead with empathy, a collaborative spirit, and a learning mindset to work cross-functionally with engineers of all levels to build security into the software development life cycle
• Leverage creative and strategic thinking to reduce risk through secure design and simplicity, not just controls
• Possess broad security knowledge to connect the dots across domains and identify holistic ways to decrease the overall threat surface
• Are keen to distill complex security concepts into clear actions and drive consensus without direct authority
• Embody a proactive mindset to thread security throughout the product lifecycle through activities like threat modeling, secure code review, and education
• Have a strong grasp of offensive security to anticipate risks from an adversary's perspective, not just check compliance boxes
• Bring experience with modern application stacks, infrastructure, and security tools to implement pragmatic defenses
• Are practiced at collaborating cross-functionally and effectively balancing security requirements with business objectives
• Advocate for security fundamentals like least privilege, defence-in-depth, and eliminating complexity that could sub-linearly scale security through smart design

Strong candidates may also:

• Hands-on technical expertise securing complex cloud environments and microservices architectures leveraging technologies like Kubernetes, Docker, and AWS / GCP
• Exposure to offensive security techniques like vulnerability testing, bug bounty, pen testing, and red team exercises
• Familiarity with AI/ML security risks such as prompt injection, data poisoning, model extraction, etc. and mitigations
• Experience building security tools, applications, and automated tools
• Solid foundational knowledge of both software and security engineering principles and are keen to continue learning
• Excellent communication skills, able to distill complex security topics for broad audiences
• Worked and thrived in fast-paced environments, and comfortable navigating ambiguity

The annual compensation range for this role is $300,000 - $405,000 USD.

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We are looking for an Engineering Manager to join our Platform org to lead and grow teams of software engineers working on foundational platform capabilities. You'll be responsible for defining and executing the creation of shared product capabilities at the core of Anthropic's product surfaces, while maintaining clear direction and stability for your team.

You'll partner closely with product managers, engineering leadership, talented engineers and research teams to transform emerging AI capabilities into platform capabilities. Success in this role requires a strong ability to understand stakeholder needs, identify opportunities to share capabilities across products, understand our product and roadmap deeply, and the ability to facilitate rapid iterations to improve our product suite.

About Product Foundations:

Product Foundations serves as an internal capabilities team building product infrastructure, shared components and focusing significant energy on cross functional efforts including reliability, latency and efficiency. Our mandate is to build and maintain the foundational platforms, infrastructure and abstractions that enable Anthropic's products to operate securely, reliably, and efficiently at scale while accelerating product development across the organisation. We embed with product engineering teams to provide platform perspective, build shared mvp capabilities, and align to a shared vision for success.

Responsibilities:

• Lead and coach a high-performing team of software engineers through the complexities of 0-1 platform development
• Partner effectively with engineering and product leaders to align on direction and execution
• Create a balanced environment that encourages both iterative improvement and rigorous evaluation
• Provide clear, actionable feedback and support for engineer growth and development
• Help partner teams develop approaches for sharing capabilities and partnering to evolve our platform alongside the sophistication of our products and users
• Drive adoption of platform capabilities and learnings to inform company-wide product strategy and planning
• Represent the platform perspective and roadmap in discussions with research, product, and leadership stakeholders

You may be a good fit if you have:

• Have 3+ years of engineering management experience leading high-performing teams in ambiguous, early-stage environments
• Excel at creating psychological safety and helping teams navigate uncertainty
• Demonstrate strong interpersonal skills and ability to guide teams through rapidly evolving organisation priorities while building underlying stable platforms
• Have excellent cross-functional leadership skills to build alignment between research, engineering and product
• Are skilled at facilitating decision-making rather than imposing solutions
• Have expertise in mentoring and investing energy into team culture
• Have excellent communication skills to represent the importance of and need to invest in platform capabilities at the core of our products
• Have a comprehensive technical understanding of modern software product development processes and technical stacks. Experience of AI/ML is a bonus
• Care deeply about responsibly pushing the boundaries of AI capabilities in service of Anthropic's mission

Strong candidates may also have experience with:

• Building products from zero to one in a startup environment
• Expertise in modern web development stacks (React, Next.js, etc)
• Experience working on AI/ML products
• Experience with identity management, authentication systems, and enterprise security standards

Deadline to apply:

None. Applications will be reviewed on a rolling basis.

Logistics

Education requirements:

We require at least a Bachelor's degree in a related field or equivalent experience.

Location-based hybrid policy:

Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

Visa sponsorship:

We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

We encourage you to apply even if you do not believe you meet every single qualification.

Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work.

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Anthropic's mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

About the Role

Claude has your back. AIRE has Claude's. Help us keep Claude reliable for everyone who depends on it.

AIRE (AI Reliability Engineering) partners with teams across Anthropic to improve reliability across our most critical serving paths -- every hop from the SDK through our network, API layers, serving infrastructure, and accelerators and back. We jump into the trenches alongside partner teams to make the systems that deliver Claude more robust and resilient, be it during an incident or collaborating on projects.

Reliability here is an emergent phenomenon that transcends any single team's boundaries, so someone has to zoom out and look at the whole picture. That's us -- and it means few teams at Anthropic offer this kind of dynamic, cross-cutting exposure to the systems that matter most.

Responsibilities

• Develop appropriate Service Level Objectives for large language model serving systems, balancing availability and latency with development velocity.
• Design and implement monitoring and observability systems across the token path.
• Assist in the design and implementation of high-availability serving infrastructure across multiple regions and cloud providers
• Lead incident response for critical AI services, ensuring rapid recovery, thorough incident reviews, and systematic improvements.
• Support the reliability of safeguard model serving -- critical for both site reliability and Anthropic's safety commitments.

You may be a good fit if you

• Have strong distributed systems, infrastructure, or reliability backgrounds -- we're looking for reliability-minded software engineers and SREs.
• Are curious and brave -- comfortable jumping into unfamiliar systems during an incident and helping drive resolution even when you don't have deep expertise yet.
• Think holistically about how systems compose and where the seams are.
• Can build lasting relationships across teams -- our engagement model depends on being welcomed as teammates, not outsiders with opinions.
• Care about users and feel ownership over outcomes, even for systems you don't own.
• Have excellent communication and collaboration skills -- you'll be partnering across the entire company.
• Bring diverse experience -- the team's strength comes from people who've built product stacks, scaled databases, run massive distributed systems, and everything in between.

Strong candidates may also

• Have been an SRE, Production Engineer, or in similar reliability-focused roles on large scale systems
• Have experience operating large-scale model serving or training infrastructure (>1000 GPUs).
• Have experience with one or more ML hardware accelerators (GPUs, TPUs, Trainium).
• Understand ML-specific networking optimizations like RDMA and InfiniBand.
• Have expertise in AI-specific observability tools and frameworks.
• Have experience with chaos engineering and systematic resilience testing.
• Have contributed to open-source infrastructure or ML tooling.

Logistics

Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience. Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

Salary

The annual compensation range for this role is €235.000 - €295.000EUR.

How we're different

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and engineering as it does with computer science. We strive to build a team that reflects this perspective, with people from a wide range of backgrounds and disciplines.

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As a member of the Applied AI team at Anthropic, you will be a Forward Deployed Engineer (FDE) who embeds directly with our most strategic federal civilian (and, occasionally, state and local) customers to drive transformational AI adoption. You will collaborate closely with customer teams to ship advanced AI applications that solve real world business problems.

Working closely with our Post-Sales, Product, and Engineering teams, you'll combine engineering expertise, an understanding of frontier AI applications, and customer-facing skills to understand customer workflows and develop innovative solutions that address complex business challenges while maintaining our high standards for safety and reliability.

You will sit at the frontier of government AI deployments and serve as one of our founding FDEs who helps to shape our forward-deployed motion. We expect our FDEs to operate autonomously, thrive under ambiguity, and represent Anthropic at the highest level in customer environments. This is a significant responsibility: you’ll play a key role in championing our mission in the enterprise.

Core Responsibilities:

• Work within customer systems to build production applications with Claude models, ensuring that these products meet customer requirements.
• Deliver technical artifacts for customers like MCP servers, sub-agents, and agent skills that will be used in production workflows.
• Provide white glove deployment support for Anthropic products in federal government environments.
• Identify and codify repeatable deployment patterns and contribute insights back to our Product and Engineering teams.
• Maintain strong knowledge of the latest developments in LLM capabilities, implementation patterns, and AI product development stacks.
• Build long term relationships with customers and proactively identify new opportunities for AI deployment throughout the lifecycle of an engagement.
• Travel frequently (25-50%) to customer sites to build in person with customers.
• Be a champion for Anthropic’s mission in the field.

You Might Be a Good Fit If You Have:

• Security clearance not required, but a plus
• Must have prior experience working with US federal civilian, state, or local agencies
• 4+ years of experience in a technical, customer facing role such as Forward Deployed Engineer, or as a Software Engineer with consulting experience. Former technical founders are also encouraged to apply.
• Production experience with LLMs including advanced prompt engineering, agent development, evaluation frameworks, and deployment at scale.
• Strong programming skills with proficiency in Python (and ideally in one or more additional languages like TypeScript, Java, etc) and experience shipping production applications
• High agency with an ability to navigate ambiguity present in complex organizations.
• High cooperation mindset for cross-organizational collaboration, balancing competing priorities with integrity.
• Passion for advancing safe, beneficial AI systems through creative technical applications.
• Strong communication skills to conduct discovery with customers and to convey technical concepts to diverse stakeholders while maintaining a low ego and collaborative approach.
• Experience with government IT systems and/or AI deployment patterns is a plus.

Logistics

• Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience.
• Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
• Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
• We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work.
• Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before you start working with us.

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You will own the vision and roadmap for Replit's GTM systems—including CRM and CPQ—while partnering closely with Finance and Legal on adjacent billing, order management, and revenue recognition workflows. You'll lead a growing team of systems professionals and collaborate across Sales, Marketing, Engineering, and other stakeholders to deliver scalable solutions that support both day-to-day commercial operations and board-level reporting.

This is a role for someone who has built and scaled GTM systems at organisations generating billions in revenue, understands the rigor required for public company controls and compliance, and thrives at the intersection of technology strategy and business operations.

Responsibilities

• Define and execute the long-term vision and roadmap for Replit's GTM systems, with direct ownership of CRM and CPQ platforms
• Own the Salesforce platform strategy and architecture, ensuring it scales to support complex enterprise sales motions, consumption-based pricing models, and multi-geo operations
• Partner with Finance, Legal, and Deal Desk on billing, order management, and revenue recognition systems and workflows, ensuring GTM systems feed accurate and timely data into downstream processes
• Establish systems and controls that meet public company reporting standards, including SOX-readiness for GTM-related processes and data flows
• Build, mentor, and lead a high-performing team of GTM systems professionals, fostering a culture of operational excellence and continuous improvement
• Drive cross-functional alignment across Sales, Marketing, Finance, Legal, and Engineering to ensure systems investments support business priorities and regulatory requirements
• Evaluate, select, and integrate best-in-class technologies into the revenue tech stack, making thoughtful build-vs-buy decisions as the organisation scales
• Develop data governance frameworks and ensure data integrity across all GTM systems, enabling reliable forecasting, pipeline management, and revenue reporting
• Leverage AI and automation to enhance system capabilities, reduce manual processes, and unlock productivity gains across revenue-generating functions
• Establish and maintain strong vendor relationships, negotiating contracts and managing third-party implementation partners

Requirements

• 15+ years of experience in GTM systems, revenue operations, or business systems, with at least 7 years in a leadership role managing teams
• Have built and scaled GTM systems infrastructure at organisations generating $1B+ in annual revenue
• Possess deep expertise in Salesforce architecture, including experience with enterprise-scale implementations supporting complex sales processes and integrations
• Have hands-on experience partnering on quote-to-cash processes (billing, order management, revenue recognition) and understand how CRM and CPQ systems integrate with downstream financial workflows
• Have direct experience supporting public company reporting requirements, SOX compliance, and audit readiness for GTM-related systems and controls
• Demonstrate a track record of effective cross-functional partnership with Finance, Legal, Sales Leadership, and Engineering teams
• Bring strong people leadership skills with experience building and developing teams in fast-paced, high-growth environments
• Can seamlessly move between strategic planning and hands-on technical problem-solving
• Communicate complex technical concepts clearly to executive and non-technical audiences

Bonus Qualifications

• Active Replit user with understanding of developer tools and coding platforms
• Experience at a high-growth SaaS company or developer-focused platform
• Background in finance, accounting, or business operations
• Experience with sales enablement and training programs
• Experience with consumption-based or usage-based revenue models in addition to traditional SaaS contract structures
• Bring familiarity with modern revenue tech stacks including tools like Stripe, Metronome, Nue.io, Workday Financials, or similar platforms
• Have experience integrating AI/ML capabilities into business systems to drive automation and predictive insights
• Hold relevant certifications such as Salesforce Architect credentials
• Have experience with international GTM operations and multi-currency, multi-entity commercial systems

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Location

Singapore

Employment Type

Full time

Location Type

Hybrid

Department

Model Deployment for Business

About the team OpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We operate at the intersection of customer delivery and core platform development.

About the role Forward Deployed Engineers (FDEs) lead complex end-to-end deployments of frontier models in production alongside our most strategic customers. You will own discovery, technical scoping, system design, build, and production rollout, partnering directly with customer engineering and domain teams.

You will measure success through production adoption, measurable workflow impact, and eval-driven feedback that changes product and model roadmaps. You’ll work closely with our Product, Research, Partnerships, GRC, Security, and GTM teams.

This role is based in Singapore. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. 50% travel is expected.

In this role you will

• Own technical delivery across multiple deployments from first prototype to stable production
• Build full-stack systems that deliver customer value and sharpen how we learn
• Embed closely with customer teams, understand their needs, and guide adoption of what you build
• Scope work, sequence delivery, and remove blockers early
• Make trade-offs between scope, speed, and quality; adjust plans to protect delivery
• Contribute directly in the code when progress or clarity depends on it
• Codify working patterns into tools, playbooks, or building blocks that others can use
• Share field feedback that helps Research and Product understand where the models succeed and where they can improve
• Keep teams moving through clarity and follow-through

You might thrive in this role if you

• Bring 5+ years of engineering or technical deployment experience that includes customer-facing work
• Have scoped and delivered complex systems in fast-moving or ambiguous environments
• Write and review production-grade code across frontend and backend using Python, JavaScript, or comparable stacks
• Simplify complexity and make fast, sound decisions under pressure
• Communicate clearly with engineers, product teams, and customer stakeholders
• Spot risks early and adjust without slowing down
• Model calm and judgment when the stakes are high

About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.

Salary

$150,000 - $200,000 per year

Benefits

• 3 days in the office per week
• Relocation assistance
• 50% travel expected

Required Skills

• 5+ years of engineering or technical deployment experience
• Customer-facing work experience
• Complex system delivery experience
• Production-grade code writing and reviewing experience
• Simplifying complexity and making fast decisions under pressure

Preferred Skills

• Python, JavaScript, or comparable stacks
• Frontend and backend development experience
• Customer engineering and domain teams experience
• Product, Research, Partnerships, GRC, Security, and GTM teams experience

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About the Team

OpenAI’s mission is to ensure that artificial general intelligence (AGI) benefits all of humanity. A key part of achieving that mission is training models that deeply understand and reflect human preferences — the Human Data team is at the heart of that effort.

The Human Data engineering team creates the systems that enable scalable, high-quality human feedback. These systems are essential to how OpenAI trains and improves its most advanced models. Engineers on this team collaborate closely with world-class researchers to bring alignment techniques to life — from experimental ideas to production-ready feedback loops.

About the Role

We’re looking for software engineers to join the Human Data team and build the platforms, prototypes, tools, and infrastructure that power how our AI models are trained, aligned, and evaluated. You’ll partner with researchers and cross-functional teams to bring alignment ideas to life, influence future model training, and shape how models interact with the real world.

We’re looking for people who are excited by technical ownership, enjoy working across the stack, and are eager to solve ambiguous problems in a high-impact, fast-paced environment.

This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.

In this role, you will:

• Build and maintain robust full-stack systems for feedback collection, data labeling, and evaluation pipelines, while maintaining high levels of security.

• Translate experimental alignment research into scalable production infrastructure, including inference and model training stacks.

• Design and iterate on user-facing tools and backend services to support high-quality data workflows

• Partner with researchers, engineers, and program leads to shape feedback loops and model interaction paradigms

• Drive infrastructure improvements that enable faster iteration and scaling across OpenAI’s frontier models, from internal research tooling all the way to production ChatGPT.

You might thrive in this role if you:

• Have strong software engineering fundamentals and experience building production systems at scale

• Enjoy full-stack development with end-to-end ownership — from backend pipelines to user interfaces

• Are motivated by high-impact collaboration with research teams and solving novel, ambiguous problems

• Are excited to shape how AI systems learn from human preferences and reflect a broad range of human values

• Care deeply about inclusive tooling and building systems that enhance model safety, reliability, and usefulness

About OpenAI

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.

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San Francisco; New York City

Employment Type

Full time

Location Type

Hybrid

Department

Compensation

• $239K – $265K • Offers Equity

The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.

• Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts

• Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)

• 401(k) retirement plan with employer match

• Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)

• Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees

• 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)

• Mental health and wellness support

• Employer-paid basic life and disability coverage

• Annual learning and development stipend to fuel your professional growth

• Daily meals in our offices, and meal delivery credits as eligible

• Relocation support for eligible employees

• Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.

More details about our benefits are available to candidates during the hiring process.

This role is at-will and OpenAI reserves the right to modify base pay and other compensation components at any time based on individual performance, team or company results, or market conditions.

About this Team

We are hiring dedicated channel leaders to own and scale Paid Search or Paid Social globally. This leader will define channel strategy, oversee execution at scale, and partner cross-functionally to maximize incremental impact and long-term user value. These are high-ownership roles responsible for channel strategy, day-to-day execution, experimentation, and performance outcomes across a global portfolio.

You will partner closely with product, engineering, data science, finance, design, and broader marketing to connect out-of-product experiences to in-product journeys, improve conversion, and optimize for long-term value (LTV), not just top-of-funnel efficiency. This team thrives on rapid iteration, rigorous measurement, and creative problem solving, while keeping user value at the center of every decision.

This role is based in San Francisco. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.

In this role, you will:

• Own channel strategy and execution for either Paid Search or Paid Social, including planning, forecasting, budget pacing, and performance management across a global portfolio.

• Drive experimentation and incrementality measurement, defining hypotheses, designing tests (e.g., geo/holdout where feasible), and translating results into scalable playbooks.

• Optimize full-funnel performance, from acquisition through activation and retention, with a focus on durable unit economics (LTV/CAC, payback, cohort quality).

• Build and evolve performance systems, including reporting, decision frameworks, and operational processes that improve speed, quality, and repeatability.

• Partner cross-functionally with product, engineering, and data science to improve conversion journeys, measurement foundations, and growth tooling.

• Develop AI-enabled workflows that increase iteration velocity across creative, targeting, insights, and optimization, while maintaining quality and control.

• Expand global reach thoughtfully, incorporating localization, regional platform nuance, and market-level performance differences.

• Build AI-first creative systems, collaborating with design to rapidly prototype and test high-performing assets.

You might thrive in this role if you have:

• 8+ years of experience in growth or performance marketing, ideally in high-growth tech and/or subscription products.

• 6+ years of deep, hands-on experience owning Paid Search _or_ Paid Social at an operational and strategic level.

• A track record of launching, scaling, and optimizing paid programs at significant budget levels with clear performance outcomes.

• Experience scaling global programs across multiple languages/regions with nuanced localization strategies.

• Strong analytical and measurement skills, including comfort with experimentation, incrementality concepts, and translating analysis into decisions.

• Experience partnering cross-functionally (product, engineering, data science, finance) to ship improvements and build durable growth systems.

• A test-and-learn mindset and comfort operating in fast-moving, ambiguous environments.

• Excellent stakeholder management and communication skills, with the ability to align teams around goals, tradeoffs, and execution plans.

• Experience with marketing tooling, BI, and measurement stacks (e.g., analytics, experimentation platforms, internal reporting), plus a willingness to adopt AI-enabled workflows.

About OpenAI

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products.

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About the role

The Manager of Post-Sales Enablement owns the strategy, execution, and continuous improvement of enablement programs for Customer Success, Support, and Services teams. This role ensures customer-facing teams have the skills, processes, and tools to accelerate time-to-value, drive adoption, improve retention, and deliver consistent, high-quality customer experiences.

Reporting to the Head of Revenue Enablement, this role is highly strategic and requires the ability to align enablement efforts with company-wide growth initiatives, influence senior leadership, and drive measurable impact on revenue outcomes. It is expected to operate at both the strategic and executional level, ensuring that enablement programs are not only designed but also successfully embedded in the field.

You’ll partner closely with Services & CS leadership, RevOps, Product, and Executive stakeholders to embed best practices, streamline workflows, and measure impact across all stages of the post-sales customer journey. While initially an individual contributor role, this position will scale into a leadership role as the company grows.

Key Responsibilities

Cross-Functional Alignment

• Partner with CRO, CS/Services leadership, RevOps, Product, and PMM to ensure alignment with GTM and customer experience priorities.

• Act as a strategic advisor on post-sales performance and field readiness.

• Proactively partner directly with senior leaders within the post-sales org to create programs and materials that improve the post-sales workflow.

Strategy & Program Execution

• Build and execute a global post-sales enablement strategy aligned to customer outcomes and retention goals.

• Implement and drive adoption of our customer engagement process, activity frameworks, and value realization practices.

• Develop training, onboarding, and ongoing skill development programs for the post-sales roles.

Field Engagement & Process Optimization

• Shadow customer calls, onboarding sessions, and support interactions to identify gaps and opportunities.

• Develop playbooks for onboarding, adoption, renewal readiness, escalation management, and customer health.

• Standardize best practices for QBRs, success planning, and issue resolution.

Tools, AI & Automation

• Partner with CS Ops/RevOps to integrate enablement tools and streamline workflows.

• Drive adoption of post-sales systems (e.g., Planhat, Salesforce, Omni).

• Identify opportunities to use AI and automation to reduce friction and improve efficiency.

Measurement & Insights

• Analyze performance data and adjust enablement programs based on insights.

• Review data to understand behavior change and recommend reinforcement or training programs to increase performance.

Experience Requirements

• 7–10 years in post-sales enablement, Customer Success, Support, Services, or related fields.

• Experience implementing customer success methodologies and driving adoption across global teams.

• Strong background in training, onboarding, and process optimization.

• Proficiency with CS/Support tech stacks and enablement platforms (e.g., CSPs, Salesforce).

• Ability to influence senior leaders and drive cross-functional alignment on complex projects.

• Experience in fast paced, high-growth environments.

• Comfort building from scratch and proven ability to scale programs over time.

Salary

We are targeting a salary range of $120,000 - $160,000, depending on experience.

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About the role

The Senior Manager of Post-Sales Enablement owns the strategy, execution, and continuous improvement of enablement programs for Customer Success, Support, and Services teams. This role ensures customer-facing teams have the skills, processes, and tools to accelerate time-to-value, drive adoption, improve retention, and deliver consistent, high-quality customer experiences.

Reporting to the Head of Revenue Enablement, this role is highly strategic and requires the ability to align enablement efforts with company-wide growth initiatives, influence senior leadership, and drive measurable impact on revenue outcomes. It is expected to operate at both the strategic and executional level, ensuring that enablement programs are not only designed but also successfully embedded in the field.

You’ll partner closely with Services & CS leadership, RevOps, Product, and Executive stakeholders to embed best practices, streamline workflows, and measure impact across all stages of the post-sales customer journey. While initially an individual contributor role, this position will scale into a leadership role as the company grows.

Key Responsibilities

Cross-Functional Alignment

• Partner with CRO, CS/Services leadership, RevOps, Product, and PMM to ensure alignment with GTM and customer experience priorities.

• Act as a strategic advisor on post-sales performance and field readiness.

• Proactively partner directly with senior leaders within the post-sales org to create programs and materials that improve the post-sales workflow.

Strategy & Program Execution

• Build and execute a global post-sales enablement strategy aligned to customer outcomes and retention goals.

• Implement and drive adoption of our customer engagement process, activity frameworks, and value realization practices.

• Develop training, onboarding, and ongoing skill development programs for the post-sales roles.

Field Engagement & Process Optimization

• Shadow customer calls, onboarding sessions, and support interactions to identify gaps and opportunities.

• Develop playbooks for onboarding, adoption, renewal readiness, escalation management, and customer health.

• Standardize best practices for QBRs, success planning, and issue resolution.

Tools, AI & Automation

• Partner with CS Ops/RevOps to integrate enablement tools and streamline workflows.

• Drive adoption of post-sales systems (e.g., Planhat, Salesforce, Omni).

• Identify opportunities to use AI and automation to reduce friction and improve efficiency.

Measurement & Insights

• Analyze performance data and adjust enablement programs based on insights.

• Review data to understand behavior change and recommend reinforcement or training programs to increase performance.

Experience Requirements

• 7–10 years in post-sales enablement, Customer Success, Support, Services, or related fields.

• Experience implementing customer success methodologies and driving adoption across global teams.

• Strong background in training, onboarding, and process optimization.

• Proficiency with CS/Support tech stacks and enablement platforms (e.g., CSPs, Salesforce).

• Ability to influence senior leaders and drive cross-functional alignment on complex projects.

• Experience in fast-paced, high-growth environments.

• Comfort building from scratch and proven ability to scale programs over time.

Salary

We are targeting a salary range of $120,000 - $160,000, depending on experience.

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Location

San Francisco

Employment Type

Full time

Location Type

Hybrid

Department

Consumer Products

Compensation

• $293K – $325K • Offers Equity

The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.

Benefits

• Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts

• Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)

• 401(k) retirement plan with employer match

• Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)

• Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees

• 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)

• Mental health and wellness support

• Employer-paid basic life and disability coverage

• Annual learning and development stipend to fuel your professional growth

• Daily meals in our offices, and meal delivery credits as eligible

• Relocation support for eligible employees

• Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.

About the Team

The Software Engineering Embedded team builds reliable, high-performance systems on custom hardware. We work closely with hardware engineers to design, optimize, and ship software that bridges cutting-edge devices and real-world constraints like memory, power, and latency. Our work spans early prototyping through product launch, ensuring that our embedded platforms are robust, efficient, and production-ready.

About the Role

As an Embedded Software Engineer, you will design, implement, and debug software for embedded devices. You’ll own low-level bring-up, write production C/C++ code, and partner closely with hardware teams to deliver reliable, high-performance systems.

We’re looking for engineers with deep embedded expertise, strong debugging skills, and a passion for building systems that perform under real-world conditions.

This role is based in San Francisco, CA. We use a hybrid work model of four days in the office per week and offer relocation assistance to new employees.

In this role, you will:

• Design, implement, and debug software for embedded devices.

• Contribute to defining software requirements, interfaces, and test plans.

• Bring up and debug new boards.

• Analyze performance, memory, and power profiles and implement optimizations.

• Investigate field issues, perform root-cause analysis, and deliver robust fixes.

• Foster good software engineering practices.

You might thrive in this role if you:

• Have deep experience shipping embedded systems (around 10+ years).

• Are proficient in C and C++.

• Are familiar with embedded toolchains, operating systems, and debugging tools.

• Have experience with both rapid prototyping and scalable product development.

• (Nice to have) Have experience with Zephyr RTOS.

• (Nice to have) Have worked with networking/wireless stacks (BLE, Wi-Fi).

• (Nice to have) Have experience with robotic system bring-up or Linux kernel development.

About OpenAI

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.

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Frontend Software Engineer, Codex App

Location

San Francisco; London, UK; Seattle

Employment Type

Full time

Department

Applied AI

Compensation

• $230K – $385K • Offers Equity

The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.

• Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts

• Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)

• 401(k) retirement plan with employer match

• Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)

• Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees

• 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)

• Mental health and wellness support

• Employer-paid basic life and disability coverage

• Annual learning and development stipend to fuel your professional growth

• Daily meals in our offices, and meal delivery credits as eligible

• Relocation support for eligible employees

• Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.

More details about our benefits are available to candidates during the hiring process.

This role is at-will and OpenAI reserves the right to modify base pay and other compensation components at any time based on individual performance, team or company results, or market conditions.

About the Team

The Codex App team builds and maintains the Codex desktop app and IDE extension — the primary ways developers interact with Codex. Our goal is to make AI feel like a real software engineering teammate inside real workflows: editing code, running tasks, reviewing changes, and coordinating long-running work.

We sit at the intersection of research, product, and design. We ship quickly, learn from real usage, and continuously refine both the experience and the harness that connects users to the model.

About the Role

We’re hiring a Frontend Software Engineer to build a top-tier desktop experience and push forward the interface for working with agents. This is a craft-heavy role: you’ll partner closely with design to prototype, iterate, and polish new interaction models — then turn them into reliable, high-performance product.

You’ll help define what great looks like for “human ↔ agent” collaboration: what belongs in the UI, how state is represented, how progress and uncertainty are communicated, and how users stay oriented across long-running and multi-step work.

What You’ll Do

• Build and ship polished, high-performance UI across the Codex desktop app and IDE extension.

• Partner tightly with design to turn prototypes into production-quality experiences (layout, motion, typography, interaction details).

• Iterate on future interfaces for interacting with agents: delegation, task timelines, status/progress, handoffs, review, and control surfaces.

• Own frontend architecture decisions (component systems, state management, navigation, rendering performance).

• Improve quality and reliability through testing, instrumentation, and thoughtful UX for failure modes.

• Collaborate with platform/model/backend partners to integrate new capabilities into cohesive product flows.

You Might Thrive Here If You

• Have strong experience with modern frontend stacks (React, TypeScript) and a high bar for UI craft.

• Love design engineering: sweating the details while keeping velocity.

• Have built desktop-caliber product experiences (Electron or similar), and care about performance, responsiveness, and “it just feels right.”

• Enjoy exploring ambiguous problems and iterating rapidly with design and product.

• Think in end-to-end workflows, not isolated screens.

• Have experience with developer tools or IDE extensions (nice-to-have).

About OpenAI

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.

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Camera ISP Software Engineer, Consumer Devices

Location

San Francisco

Employment Type

Full time

Department

Consumer Products

Compensation

• $293K – $325K • Offers Equity

The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.

• Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts

• Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)

• 401(k) retirement plan with employer match

• Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)

• Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees

• 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)

• Mental health and wellness support

• Employer-paid basic life and disability coverage

• Annual learning and development stipend to fuel your professional growth

• Daily meals in our offices, and meal delivery credits as eligible

• Relocation support for eligible employees

• Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.

More details about our benefits are available to candidates during the hiring process.

This role is at-will and OpenAI reserves the right to modify base pay and other compensation components at any time based on individual performance, team or company results, or market conditions.

About the Team

The Consumer Products team at OpenAI builds and ships end-to-end hardware and software experiences that bring frontier AI into the physical world. We work across industrial design, hardware engineering, embedded systems, and AI research to create category-defining consumer devices that feel intuitive, reliable, and deeply integrated with OpenAI’s models.

Within this organisation, the Camera team is responsible for delivering robust, production-ready imaging systems that operate under real-world constraints such as motion, power, latency, and manufacturing variation. Our work spans early silicon and board bring-up through mass production, and directly supports both user-facing experiences and on-device perception for AI-driven features.

We operate as a small, highly technical team with deep ownership, close cross-functional collaboration, and a strong bias toward shipping high-quality products rather than incremental demos.

About the Role

As a Camera ISP Software Engineer, you will own end-to-end ISP bring-up and tuning across prototype and production hardware. You’ll work across software tuning and hardware-accelerated pipelines to deliver stable, high-quality imaging under real-world constraints such as motion, power, and manufacturing variation.

This role is ideal for engineers who thrive in ambiguous early-stage environments, enjoy deep technical ownership, and take pride in shipping production-grade imaging systems.

This role is based in San Francisco, CA. We use a hybrid work model of four days in the office per week and offer relocation assistance to new employees.

In this role, you will:

• Own end-to-end ISP tuning and bring-up, from early prototypes through production hardware.

• Tune core 3A and image-quality blocks including AE, AWB, AF, noise reduction (spatial and temporal), sharpening, tone mapping, color correction, HDR/WDR, flicker mitigation, lens shading, defect pixel correction, and related ISP stages.

• Build repeatable capture and evaluation workflows, combining controlled lab sweeps with real-world validation.

• Validate robustness across sensor, module, and manufacturing variation with clear, defensible success criteria.

• Deliver production-grade tuning artifacts, including versioned tuning packs, parameter manifests, change logs, and curated RAW and processed datasets with supporting documentation.

• Partner closely with camera firmware, systems, and hardware teams to debug pipelines, configure sensors, and resolve board-level and silicon-level issues as designs evolve.

You might thrive in this role if you:

• Deep experience shipping ISP tuning for embedded or mobile camera products, from bring-up through production.

• Strong fundamentals across 3A (AE/AWB/AF), noise modeling, sharpening and detail trade-offs, tone mapping, and color pipelines.

• Proven ability to run data-driven tuning loops, including repeatable capture, rigorous evaluation, and disciplined versioning of tuning artifacts.

• Hands-on experience debugging end-to-end camera pipelines on real hardware, including RAW capture, processed outputs, and hardware-accelerated paths.

• Ability to collaborate cross-functionally and translate system-level constraints (power, latency, motion, reliability) into concrete tuning decisions and validation plans.

Preferred Qualifications

• Experience with common mobile or embedded SoC camera stacks and vendor frameworks.

• Experience tuning imaging pipelines explicitly for downstream machine-learning consumers, with iteration driven by model feedback.

• Experience designing motion-aware temporal imaging strategies that remain stable under rapid device or scene motion.

Experience Level

Mid

Employment Type

Full time

Workplace Type

Hybrid

Category

Engineering

Industry

Technology

Salary Range

$293K – $325K

Required Skills

• Camera ISP tuning
• Embedded systems
• AI research
• Industrial design
• Hardware engineering
• Machine learning
• Image processing
• Computer vision

Preferred Skills

• Mobile or embedded SoC camera stacks
• Vendor frameworks
• Imaging pipelines
• Motion-aware temporal imaging strategies
• Downstream machine-learning consumers
• Model feedback
• System-level constraints
• Power
• Latency
• Motion
• Reliability

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About the Role

As a Camera Firmware Engineer, you will own low-level camera enablement on custom hardware—from early board bring-up through stable production capture. You will develop and maintain the firmware and software that makes camera sensors reliable, controllable, and debuggable, forming the foundation for higher-level camera pipelines and product features.

In This Role, You Will

• Bring up new camera sensors and modules on prototype and production boards, including link stability, sensor control, and correct power, reset, and clock sequencing.

• Develop and maintain low-level camera software, including sensor drivers, board configuration, and camera subsystem integration across hardware revisions.

• Enable and validate core capture paths for development and production, including RAW capture for debugging, still capture, and hardware-accelerated video encode and streaming with stable timestamps and long-duration reliability.

• Stand up camera control and repeatability features, including basic 3A loop exposure, manual overrides and locks, and deterministic presets to support validation and debugging.

• Build and maintain camera bring-up tooling, such as capture scripts, automated sweeps, manifests, and debugging utilities that make issues reproducible and easy to triage.

• Partner closely with electrical engineering, camera pipeline owners, and systems teams to define interfaces, unblock integration, and keep the camera stack stable as the device evolves.

You might thrive in this role if you:

• Deep experience shipping embedded camera systems, including sensor bring-up, driver development, and board-level debugging.

• Strong C/C++ experience with embedded or Linux-based systems; comfortable debugging across kernel and userspace boundaries.

• Hands-on understanding of common camera hardware interfaces (for example, MIPI CSI and sensor control buses) and the practical realities of bring-up, including power, reset, clocking, and sequencing.

Preferred Qualifications

• Experience with common mobile or embedded SoC camera stacks and vendor frameworks.

• Experience integrating and debugging hardware acceleration blocks adjacent to camera pipelines, such as video encode and decode paths.

• Familiarity building higher-level capture pipelines (for example, GStreamer) on top of low-level camera enablement.

About OpenAI

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of artificial intelligence research and deployment.

XML job scraping automation by YubHub

Location

San Francisco

Employment Type

Full time

Department

Applied AI

Compensation

• $230K – $385K • Offers Equity

The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.

Benefits

• Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts

• Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)

• 401(k) retirement plan with employer match

• Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)

• Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees

• 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)

• Mental health and wellness support

• Employer-paid basic life and disability coverage

• Annual learning and development stipend to fuel your professional growth

• Daily meals in our offices, and meal delivery credits as eligible

• Relocation support for eligible employees

• Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.

About the Team:

The Database Systems team specializes in high-performance distributed databases. Our team built Rockset, the real-time search, analytics, and vector database that powers all vector search and retrieval augmented generation (RAG) at OpenAI. In addition to retrieval, as an online database, Rockset powers core functionality across all of OpenAI's product lines and many critical internal use cases.

About the Role:

We are looking for engineers passionate about distributed systems, close-to-the-metal performance optimization (our core engine is written in C++), and building scalable database infrastructure from the ground up. As an engineer on the Database Systems team, you'll contribute to the core database engine, driving improvements across ingestion, query execution, indexing, and storage. You'll partner with teams across OpenAI to unlock new product capabilities and help scale online database reliability and throughput as usage grows by orders of magnitude.

In this role you will:

• Design, build, and operate high-performance distributed systems

• Identify and resolve performance bottlenecks to scale infrastructure to the next order of magnitude

• Define long-term technical direction and guide system evolution

• Collaborate with product, engineering, and research teams to deliver scalable and reliable infrastructure

• Dig deep into complex production issues across the stack

• Contribute to incident response, postmortems, and best practices for system reliability

You might thrive in this role if you:

• Have significant experience building, scaling, and optimizing distributed systems at scale

• Are curious about database internals, storage engines, or low-latency query systems

• Enjoy debugging challenging performance issues in complex, high-throughput systems

• Have experience operating production clusters at scale (e.g., Kubernetes or other orchestration systems)

• Think rigorously about scalability, correctness, and reliability

• Thrive in fast-paced environments with high autonomy and impact

Qualifications:

• 4+ years of relevant industry experience, with 2+ years leading large scale, complex projects or teams as an engineer or tech lead

• Experience with distributed systems at scale, with a strong focus on performance, reliability, and scalability

• Strong communication skills and ability to collaborate across highly technical and cross-functional teams

• Proficiency in a systems programming language such as C++ (our core engine is written in C++) is strongly preferred

• Fluency in cloud environments (AWS, GCP, Azure) and IaC tools (Terraform or similar)

• Experience with Linux systems, CI/CD pipelines, and modern observability stacks (Prometheus, Grafana, etc.)

• Domain knowledge in areas such as databases, data systems, storage engines, indexing, and query processing is a plus but not required

About OpenAI

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.

XML job scraping automation by YubHub

Location

San Francisco

Employment Type

Full time

Department

Consumer Products

Compensation

• $293K – $325K • Offers Equity

The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.

• Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts

• Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)

• 401(k) retirement plan with employer match

• Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)

• Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees

• 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)

• Mental health and wellness support

• Employer-paid basic life and disability coverage

• Annual learning and development stipend to fuel your professional growth

• Daily meals in our offices, and meal delivery credits as eligible

• Relocation support for eligible employees

• Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.

More details about our benefits are available to candidates during the hiring process.

This role is at-will and OpenAI reserves the right to modify base pay and other compensation components at any time based on individual performance, team or company results, or market conditions.

Location: San Francisco, CA (Hybrid: 4 days onsite/week). Relocation assistance available.

About the Team:

We build foundational platform software that enables reliable, secure, and performant products. The team works across system layers and partners closely with adjacent engineering groups to deliver robust capabilities from concept through launch.

About the Role:

We’re seeking a Systems Software Engineer to design, implement, and debug core platform components and the pipelines that build and update system images. You’ll work across operating system layers, focusing on performance, security, and deep system debugging to ship production‑grade systems.

In this role, you will:

• Design, implement, and debug system‑level components and services across kernel and user space.

• Configure and maintain OS platform services (init, services, networking, security policies) and related tooling.

• Build and operate image and update pipelines, ensuring reliability, reproducibility, and rollback safety.

• Instrument and analyze performance using profiling and tracing; optimize CPU, memory, I/O, and power usage.

• Own platform observability and reliability: logging, crash capture, watchdogs, and diagnostics.

• Collaborate with cross‑functional teams to define interfaces and deliver end‑to‑end features.

• Establish strong engineering practices: code review, CI, reproducible builds, and release management.

• Partner with external suppliers to support builds and deployments.

You might thrive in this role if you:

• Have shipped production systems software on modern operating systems.

• Are proficient in C/C++ and a scripting language, and comfortable with OS internals (concurrency, memory management, filesystems, networking, power management).

• Bring strong systems debugging skills using debuggers, tracers, profilers, and logs across kernel/user‑space boundaries.

• Understand configuration of platform services and interfaces, and can translate requirements into stable, well‑documented APIs.

• Are fluent in user‑space foundations (service management, IPC, networking, packaging, automation).

• Have experience building platform images and designing update mechanisms for reliability and security.

Preferred Qualifications:

• Exposure to platform security (secure boot, sandboxing, mandatory access controls, attestation).

• Experience with graphics/media, hardware acceleration, or high‑throughput data paths.

• Familiarity with connectivity stacks and network configuration.

• Observability and diagnostics in distributed or resource‑constrained environments.

• Work on open‑source platforms or contributions to systems projects.

About OpenAI

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.

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What you'll do

Build and evolve full stack systems that integrate multiple third-party and in-house Sonar models, ensuring seamless orchestration, robustness, and observability in production.

What you need

• Hands-on experience building production AI or agentic applications end to end, including tool calling, context engineering, and integration with modern LLM APIs.

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The program's goal is to encourage qualified researchers with overseas experience who have excelled in their fields through high-level science and technology-oriented research to come to Türkiye and contribute to projects that will be carried out in research areas of strategic importance for our country.

What you need

Applicants must meet at least one of the following requirements:

• To be on the "Top Cited Researchers List" published by Thomson Reuters in any year of the last 5 years.
• To have worked for a total of at least 30 months in institutions ranked in one of the following positions in the last 5 years:
• List of top 100 universities published by QS (Quacquarelli Symonds) or THE (Times Higher Education).
• List of top 2500 companies with the highest R&D spending in the world published by the European Commission Joint Research Centre:
• List of top 250 institutions in the health - higher education - public - private subfields published by Scimago Institutions Ranking
• List of most successful Start-Ups and Unicorn Companies receiving the highest investment.

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What you'll do

• Design, develop, and maintain scalable APIs and automation services in Python and/or Go to manage platform operations (e.g., provisioning, configuration, access control, DNS updates).
• Automate infrastructure lifecycle workflows across Kubernetes/OpenShift and related systems.

What you need

• 5+ years of professional software engineering experience using Python and/or Go (Golang).
• Proven experience designing and implementing RESTful or gRPC APIs.

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What you'll do

• Architect, implement, and manage resilient, scalable, and highly available infrastructure systems.
• Lead initiatives to automate manual operations, deployment, and monitoring processes to improve reliability and reduce toil.

What you need

• Strong proficiency in Linux/Unix system administration and internals.
• Proven experience in cloud platforms — AWS, Azure, or GCP.

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