Your responsibilities will include serving as the primary technical point of contact for customers, establishing strong technical relationships and ensuring their success with CoreWeave's cloud infrastructure offerings.

You will collaborate closely with customers to understand their unique business needs and create, prototype, and deploy tailored solutions that align with their requirements.

You will lead proof of concept initiatives to showcase the value and viability of CoreWeave's solutions within specific environments.

You will drive technical leadership and direction during customer meetings, presentations, and workshops, addressing any technical queries or concerns that arise.

You will act as a virtual member of CoreWeave's Kubernetes product and engineering teams, identifying opportunities for product enhancement and collaborating with engineers to implement your suggestions.

You will offer valuable insights on product features, functionality, and performance, contributing regularly to discussions about product strategy and architecture.

You will conduct periodic technical reviews and assessments of customer workloads, pinpointing opportunities for workload optimization and suggesting suitable solutions.

You will stay informed of the latest developments and trends in Kubernetes, cloud computing and infrastructure, sharing your thought leadership with customers and internal stakeholders.

You will lead the prototyping and initiation of research and development efforts for emerging products and solutions, delivering prototypes and key insights for internal consumption.

You will represent CoreWeave at conferences and industry events, with occasional travel as required.

To be successful in this role, you will need to have a B.S. in Computer Science or a related technical discipline, or equivalent experience.

You will also need to have 7+ years of proven experience as a Solutions Architect, engineer, researcher, or technical account manager in cloud infrastructure, focusing on building distributed systems or HPC/cloud services, with an expertise focused on scalable Kubernetes solutions.

You will need to be fluent in cloud computing concepts, architecture, and technologies with hands-on experience in designing and implementing cloud solutions.

You will need to have a proven track record with building customer relationships, communicating clearly and the ability to break down complex technical concepts to both technical and non-technical audiences.

You will need to be familiar with NVIDIA GPUs typically used in AI/ML applications and associated technologies such as Infiniband and NVIDIA Collective Communications Library (NCCL).

You will need to have experience with running large-scale Artificial Intelligence/Machine Learning (AI/ML) training and inference workloads on technologies such as Slurm and Kubernetes.

Preferred qualifications include code contributions to open-source inference frameworks, experience with scripting and automation related to Kubernetes clusters and workloads, experience with building solutions across multi-cloud environments, and client or customer-facing publications/talks on latency, optimization, or advanced model-server architectures.

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Key Responsibilities:

• Lead and mentor engineers, fostering a culture of collaboration and continuous improvement.
• Scale logging, tracing, and metrics platforms to support a global datacenter footprint.
• Develop and refine monitoring and alerting to enhance system reliability.
• Advise engineers across CoreWeave on optimal usage of Observability systems.
• Automate interactions with CoreWeave's Compute Infrastructure layer.
• Manage production clusters and ensure development teams follow best practices for deployments.

Required Qualifications:

• 7+ years of experience in Software Engineering, Site Reliability Engineering, DevOps, or a related field.
• Deep expertise across all observability pillars using tools like ClickHouse, Elastic, Loki, Victoria Metrics, Prometheus, Thanos and/or Grafana.
• Expertise in Kubernetes, containerization, and microservices architectures.
• Proven track record of leading incident management and post-mortem analysis.
• Excellent problem-solving, analytical, and communication skills.

Preferred Qualifications:

• Experience running and scaling observability tools as a cloud provider.
• Experience administering large-scale kubernetes clusters.
• Deep understanding of data-streaming systems.

The base salary range for this role is $188,000 to $250,000.

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Your primary responsibility will be to serve as the primary technical point of contact for customers, establishing strong technical relationships and ensuring their success with CoreWeave's cloud infrastructure offerings.

You will collaborate closely with customers to understand their unique business needs and create, prototype, and deploy tailored solutions that align with their requirements.

You will lead proof of concept initiatives to showcase the value and viability of CoreWeave's solutions within specific environments.

You will drive technical leadership and direction during customer meetings, presentations, and workshops, addressing any technical queries or concerns that arise.

You will act as a virtual member of CoreWeave's Kubernetes product and engineering teams, identifying opportunities for product enhancement and collaborating with engineers to implement your suggestions.

You will offer valuable insights on product features, functionality, and performance, contributing regularly to discussions about product strategy and architecture.

You will conduct periodic technical reviews and assessments of customer workloads, pinpointing opportunities for workload optimization and suggesting suitable solutions.

You will stay informed of the latest developments and trends in Kubernetes, cloud computing and infrastructure, sharing your thought leadership with customers and internal stakeholders.

You will lead the prototyping and initiation of research and development efforts for emerging products and solutions, delivering prototypes and key insights for internal consumption.

You will represent CoreWeave at conferences and industry events, with occasional travel as required.

To be successful in this role, you will need to have a proven track record of working as a Solutions Architect, engineer, researcher, or technical account manager in cloud infrastructure, focusing on building distributed systems or HPC/cloud services, with an expertise focused on scalable Kubernetes solutions.

You will also need to have fluency in cloud computing concepts, architecture, and technologies with hands-on experience in designing and implementing cloud solutions.

In addition, you will need to have a proven track record with building customer relationships, communicating clearly and the ability to break down complex technical concepts to both technical and non-technical audiences.

Preferred qualifications include code contributions to open-source inference frameworks, experience with scripting and automation related to Kubernetes clusters and workloads, experience with building solutions across multi-cloud environments, and client or customer-facing publications/talks on latency, optimization, or advanced model-server architectures.

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Our team empowers internal and external users to understand, troubleshoot, and optimize complex AI workloads by transforming telemetry into actionable insights.

As a Senior Software Engineer on the Observability Insights team, you will lead the development of agentic interfaces and product experiences that sit atop CoreWeave's telemetry layer.

You'll design multi-tenant APIs, managed Grafana experiences, and MCP-based tool servers to help customers and internal teams interact with data in innovative ways.

Collaborating closely with PMs and engineering leadership, your work will shape the end-to-end observability experience and influence how people engage with cutting-edge AI infrastructure.

About the role

• 6+ years of experience in software or infrastructure engineering building production-grade backend systems and distributed APIs.

• Strong focus on developer-facing infrastructure, with a customer-obsessed approach to SDKs, CLIs, and APIs.

• Proficient in reliability engineering, including fault-tolerant design, SLOs, error budgets, and multi-tenant system resilience.

• Familiar with observability systems such as ClickHouse, Loki, VictoriaMetrics, Prometheus, and Grafana.

• Experienced in agentic applications or LLM-based features, including grounding, tool calling, and operational safety.

• Comfortable writing production code primarily in Go, with the ability to integrate Python components when needed.

• Collaborative experience in agile teams delivering end-to-end telemetry-to-insights pipelines.

Preferred

• Experience operating Kubernetes clusters at scale, especially for AI workloads.

• Hands-on experience with logging, tracing, and metrics platforms in production, with deep knowledge of cardinality, indexing, and query optimization.

• Experienced in running distributed systems or API services at cloud scale, including event streaming and data pipeline management.

• Familiarity with LLM frameworks, MCP, and agentic tooling (e.g., Langchain, AgentCore).

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!

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You want to build and run elegant and thorough machine learning experiments to help us understand and steer the behavior of powerful AI systems. You care about making AI helpful, honest, and harmless, and are interested in the ways that this could be challenging in the context of human-level capabilities. You could describe yourself as both a scientist and an engineer. As a Research Engineer on Alignment Science, you'll contribute to exploratory experimental research on AI safety, with a focus on risks from powerful future systems (like those we would designate as ASL-3 or ASL-4 under our Responsible Scaling Policy), often in collaboration with other teams including Interpretability, Fine-Tuning, and the Frontier Red Team.

Our blog provides an overview of topics that the Alignment Science team is either currently exploring or has previously explored. Our current topics of focus include...

• Scalable Oversight: Developing techniques to keep highly capable models helpful and honest, even as they surpass human-level intelligence in various domains.

• AI Control: Creating methods to ensure advanced AI systems remain safe and harmless in unfamiliar or adversarial scenarios.

• Alignment Stress-testing : Creating model organisms of misalignment to improve our empirical understanding of how alignment failures might arise.

• Automated Alignment Research: Building and aligning a system that can speed up & improve alignment research.

• Alignment Assessments: Understanding and documenting the highest-stakes and most concerning emerging properties of models through pre-deployment alignment and welfare assessments (see our Claude 4 System Card), misalignment-risk safety cases, and coordination with third-party evaluators.

• Safeguards Research: Developing robust defenses against adversarial attacks, comprehensive evaluation frameworks for model safety, and automated systems to detect and mitigate potential risks before deployment.

• Model Welfare: Investigating and addressing potential model welfare, moral status, and related questions. See our program announcement and welfare assessment in the Claude 4 system card for more.

_Note: For this role, we conduct all interviews in Python and prefer candidates to be based in the Bay Area._

Representative projects:

• Testing the robustness of our safety techniques by training language models to subvert our safety techniques, and seeing how effective they are at subvertinng our interventions.

• Run multi-agent reinforcement learning experiments to test out techniques like AI Debate.

• Build tooling to efficiently evaluate the effectiveness of novel LLM-generated jailbreaks.

• Write scripts and prompts to efficiently produce evaluation questions to test models’ reasoning abilities in safety-relevant contexts.

• Contribute ideas, figures, and writing to research papers, blog posts, and talks.

• Run experiments that feed into key AI safety efforts at Anthropic, like the design and implementation of our Responsible Scaling Policy.

You may be a good fit if you:

• Have significant software, ML, or research engineering experience

• Have some experience contributing to empirical AI research projects

• Have some familiarity with technical AI safety research

• Prefer fast-moving collaborative projects to extensive solo efforts

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

• Care about the impacts of AI

Strong candidates may also:

• Have experience authoring research papers in machine learning, NLP, or AI safety

• Have experience with LLMs

• Have experience with reinforcement learning

• Have experience with Kubernetes clusters and complex shared codebases

Candidates need not have:

• 100% of the skills needed to perform the job

• Formal certifications or education credentials

The annual compensation range for this role is listed below.

For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.

Annual Salary:

$350,000 \- $500,000USD

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. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.

Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruits through our website and other job boards, and we will never ask you to pay for any part of the recruitment process.

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Offensive Security Engineer, Agent Security

Location

San Francisco; New York City; Remote - US; Seattle; Washington, DC

Employment Type

Full time

Department

Security

Compensation

• San Francisco, Seattle, New York$347K – $490K • Offers Equity
• Zone A$312.3K – $490K • Offers Equity
• Zone B$277.6K – $490K • 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

Security is at the foundation of OpenAI’s mission to ensure that artificial general intelligence benefits all of humanity. The Security team protects OpenAI’s technology, people, and products. We are technical in what we build but are operational in how we do our work, and are committed to supporting all products and research at OpenAI. Our Security team tenets include: prioritizing for impact, enabling researchers, preparing for future transformative technologies, and engaging a robust security culture.

About the Role

We're seeking an exceptional Principal-level Offensive Security Engineer to challenge and strengthen OpenAI's security posture. This role isn't your typical red team job - it's an opportunity to engage broadly and deeply, craft innovative attack simulations, collaborate closely with defensive teams, and influence strategic security improvements across the organization.

You'll have the chance to not only find vulnerabilities but actively drive their resolution, automate offensive techniques with cutting-edge technologies, and use your unique attacker perspective to shape our security strategy.

This role will be primarily focused on continuously testing our agent powered products like codex and operator. These systems are uniquely valuable targets because they’re rapidly evolving, have access to perform sensitive actions on behalf of users, and have large, diverse attack surfaces. You will play a crucial role in securing our agents by hunting for realistic vulnerabilities that emerge from the interactions between the applications, infrastructure, and models that power them.

In this role you will:

• Continuously hunt for vulnerabilities in the interactions between the applications, infrastructure, and models that power our agentic products.

• Conduct open-scope red and purple team operations, simulating realistic attack scenarios.

• Collaborate proactively with defensive security teams to enhance detection, response, and mitigation capabilities.

• Perform comprehensive penetration testing on our diverse suite of products.

• Leverage advanced automation and OpenAI technologies to optimize your offensive security work.

• Present insightful, actionable findings clearly and compellingly to inspire impactful change.

• Influence security strategy by providing attacker-driven insights into risk and threat modeling.

You might thrive in this role if you have:

• 7+ years of hands-on red team experience or exceptional accomplishments demonstrating equivalent expertise.

• Deep expertise conducting offensive security operations within modern technology companies.

• Experience designing, developing, or testing assessing the security of AI-powered systems.

• Experience working finding, exploiting and mitigating common vulnerabilities in AI systems like prompt injection, leaking sensitive data, confused deputies, and dynamically generated UI components.

• Exceptional skill in code review, identifying novel and subtle vulnerabilities.

• Proven experience performing offensive security assessments in at least one hyperscaler cloud environment (Azure preferred).

• Demonstrated mastery assessing complex technology stacks, including:

• Highly customized Kubernetes clusters

• Container environments

• CI/CD pipelines

• GitHub security

• macOS and Linux operating systems

• Data science tooling and environments

• Python-based web services

• React-based frontend applications
• Strong intuitive understanding of trust boundaries and risk assessment in dynamic contexts.

• Excellent coding skills, capable of writing robust tools and automation for offensive operations.

• Ability to communicate complex technical concepts to both technical and non-technical stakeholders.

Experience Level

Senior

Employment Type

Full-time

Workplace Type

Remote

Category

Engineering

Industry

Technology

Salary Range

$347K – $490K • Offers Equity

Required Skills

• Red team experience
• Offensive security operations
• AI-powered systems security
• Vulnerability assessment
• Penetration testing
• Automation
• Code review
• Cloud security
• Kubernetes
• Container security
• CI/CD pipelines
• GitHub security
• macOS and Linux operating systems
• Data science tooling and environments
• Python-based web services
• React-based frontend applications

Preferred Skills

• Azure cloud security
• Highly customized Kubernetes clusters
• Container environments
• CI/CD pipelines
• GitHub security
• macOS and Linux operating systems
• Data science tooling and environments
• Python-based web services
• React-based frontend applications

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