In this role, you will work at the intersection of client advisory, AI product engineering, and delivery execution, helping banks, insurers, and capital markets firms transition from GenAI pilots to production-grade, governed, multi-agent systems. You will apply leading GenAI frameworks and LLM platforms , including Anthropic, OpenAI, LangChain, LangGraph, DSPy, and vector databases,while operating across the full Agentic SDLC.

P&C Insurance knowledge and experience is a significant plus. Additionally, familiarity with core insurance platforms like Guidewire, DuckCreek or Majesco will be extremely helpful to succeed in this role.

We are looking for candidates across all levels of experience and expertise - junior through senior level AI Product Engineers.

Responsibilities

• Partner directly with Financial Services clients to identify, prioritize, and shape Agentic AI use cases across customer operations, underwriting, claims, risk, compliance, finance, and technology.
• Lead client workshops to define agent personas, responsibilities, autonomy boundaries, human-in-the-loop checkpoints, and escalation logic.
• Translate evolving business needs into agentic product backlogs, roadmaps, and MVP definitions.
• Support executive conversations around GenAI platform strategy, operating models, vendor selection, and scale-out approaches.

Agentic Platform & Architecture Design

• Design and implement multi-agent architectures using modern GenAI tooling, including:
• Planner, executor, reviewer/critic, and supervisor agents
• Tool-calling and function-calling agents
• Memory-enabled agents (conversation, semantic, episodic, and structured memory)
• Leverage LangChain and LangGraph for agent orchestration, workflows, and control flow.
• Apply DSPy and declarative prompt optimization techniques for repeatability, performance tuning, and regression control.
• Design agent interaction patterns such as hierarchical agents, collaborating agents, and event-driven agent workflows.
• Define standardized agent contracts, interfaces, and schemas to enable reuse and scale.

Agentic SDLC & Engineering Delivery

• Own delivery across the full Software Development Lifecycle (SDLC), extending it into a formal Agentic SDLC, including:
• Agent design specifications and behavior contracts
• Prompt, policy, and tool versioning
• Simulation environments and offline evaluation
• Automated testing of agent flows and guardrails
• Controlled rollout, telemetry-driven optimization, and continuous learning
• Build production-grade AI services primarily using Python, integrating:
• LLM providers such as Anthropic (Claude), OpenAI, and open-source models
• Retrieval-Augmented Generation (RAG) using vector databases (e.g., Pinecone, FAISS, Milvus, Weaviate)
• Implement CI/CD pipelines for agent code, prompts, and policies.
• Integrate GenAI agents with client systems via APIs, workflow engines, event streams, and data platforms.

Observability, Evaluation & Optimization

• Implement agent observability including tracing, decision logging, tool usage, and failure analysis.
• Apply evaluation frameworks for hallucination detection, consistency checks, and fitness scoring.
• Design feedback loops incorporating human-in-the-loop review and reinforcement.
• Monitor cost, latency, throughput, and behavioral drift across deployed agents.

Governance, Risk & Financial Services Compliance

• Design Agentic AI platforms aligned with Financial Services regulatory expectations, including:
• Auditability and traceability of agent decisions
• Model and prompt explainability
• Data privacy and security controls
• Resilience and fail-safe mechanisms
• Embed guardrails and policies addressing hallucination risk, bias, unauthorized actions, and escalation failures.
• Produce documentation supporting risk, compliance, internal audit, and regulator engagement.

Team Leadership & Firm Contribution

• Provide technical leadership and mentorship to consulting delivery teams.
• Contribute to internal GenAI accelerators, agent frameworks, and reusable assets.
• Support RFPs, proposals, and client solution designs with credible GenAI and agentic architectures.
• Participate in thought leadership on Agentic SDLC, GenAI engineering, and responsible autonomy.

XML job scraping automation by YubHub

We are seeking an experienced and innovative AI Product Engineer – Agentic Platforms to join our Financial Services Artificial Intelligence & Business Lines (FS-ABL) practice. This role is ideal for a consulting technologist with deep expertise in modern GenAI tooling, agentic system design, and enterprise SDLC, who can partner directly with clients to envision, design, develop, and deploy Agentic AI platforms in regulated environments.

In this role, you will work at the intersection of client advisory, AI product engineering, and delivery execution, helping banks, insurers, and capital markets firms transition from GenAI pilots to production-grade, governed, multi-agent systems. You will apply leading GenAI frameworks and LLM platforms , including Anthropic, OpenAI, LangChain, LangGraph, DSPy, and vector databases,while operating across the full Agentic SDLC.

P&C Insurance knowledge and experience is a significant plus. Additionally, familiarity with core insurance platforms like Guidewire, DuckCreek or Majesco will be extremely helpful to succeed in this role.

We are looking for candidates across all levels of experience and expertise - junior through senior level AI Product Engineers.

Responsibilities

Client Advisory & Product Vision

Partner directly with Financial Services clients to identify, prioritize, and shape Agentic AI use cases across customer operations, underwriting, claims, risk, compliance, finance, and technology.

Lead client workshops to define agent personas, responsibilities, autonomy boundaries, human-in-the-loop checkpoints, and escalation logic.

Translate evolving business needs into agentic product backlogs, roadmaps, and MVP definitions.

Support executive conversations around GenAI platform strategy, operating models, vendor selection, and scale-out approaches.

Agentic Platform & Architecture Design

Design and implement multi-agent architectures using modern GenAI tooling, including:

Planner, executor, reviewer/critic, and supervisor agents

Tool-calling and function-calling agents

Memory-enabled agents (conversation, semantic, episodic, and structured memory)

Leverage LangChain and LangGraph for agent orchestration, workflows, and control flow.

Apply DSPy and declarative prompt optimization techniques for repeatability, performance tuning, and regression control.

Design agent interaction patterns such as hierarchical agents, collaborating agents, and event-driven agent workflows.

Define standardized agent contracts, interfaces, and schemas to enable reuse and scale.

Agentic SDLC & Engineering Delivery

Own delivery across the full Software Development Lifecycle (SDLC), extending it into a formal Agentic SDLC, including:

Agent design specifications and behavior contracts

Prompt, policy, and tool versioning

Simulation environments and offline evaluation

Automated testing of agent flows and guardrails

Controlled rollout, telemetry-driven optimization, and continuous learning

Build production-grade AI services primarily using Python, integrating:

LLM providers such as Anthropic (Claude), OpenAI, and open-source models

Retrieval-Augmented Generation (RAG) using vector databases (e.g., Pinecone, FAISS, Milvus, Weaviate)

Implement CI/CD pipelines for agent code, prompts, and policies.

Integrate GenAI agents with client systems via APIs, workflow engines, event streams, and data platforms.

Observability, Evaluation & Optimization

Implement agent observability including tracing, decision logging, tool usage, and failure analysis.

Apply evaluation frameworks for hallucination detection, consistency checks, and fitness scoring.

Design feedback loops incorporating human-in-the-loop review and reinforcement.

Monitor cost, latency, throughput, and behavioral drift across deployed agents.

Governance, Risk & Financial Services Compliance

Design Agentic AI platforms aligned with Financial Services regulatory expectations, including:

Auditability and traceability of agent decisions

Model and prompt explainability

Data privacy and security controls

Resilience and fail-safe mechanisms

Embed guardrails and policies addressing hallucination risk, bias, unauthorized actions, and escalation failures.

Produce documentation supporting risk, compliance, internal audit, and regulator engagement.

Team Leadership & Firm Contribution

Provide technical leadership and mentorship to consulting delivery teams.

Contribute to internal GenAI accelerators, agent frameworks, and reusable assets.

Support RFPs, proposals, and client solution designs with credible GenAI and agentic architectures.

Participate in thought leadership on Agentic SDLC, GenAI engineering, and responsible autonomy.

Benefits

This position comes with competitive compensation and benefits package:

1. Competitive salary and performance-based bonuses

1. Comprehensive benefits package

1. Career development and training opportunities

1. Flexible work arrangements (remote and/or office-based)

1. Dynamic and inclusive work culture within a globally known group

1. Private Health Insurance

1. Retirement Benefits

1. Paid Time Off

1. Training & Development

1. Note: Benefits differ based on employee level

XML job scraping automation by YubHub

We are seeking an experienced and innovative AI Product Engineer – Agentic Platforms to join our Financial Services Artificial Intelligence & Business Lines (FS-ABL) practice. This role is ideal for a consulting technologist with deep expertise in modern GenAI tooling, agentic system design, and enterprise SDLC, who can partner directly with clients to envision, design, develop, and deploy Agentic AI platforms in regulated environments.

In this role, you will work at the intersection of client advisory, AI product engineering, and delivery execution, helping banks, insurers, and capital markets firms transition from GenAI pilots to production-grade, governed, multi-agent systems. You will apply leading GenAI frameworks and LLM platforms , including Anthropic, OpenAI, LangChain, LangGraph, DSPy, and vector databases,while operating across the full Agentic SDLC.

P&C Insurance knowledge and experience is a significant plus. Additionally, familiarity with core insurance platforms like Guidewire, DuckCreek or Majesco will be extremely helpful to succeed in this role.

We are looking for candidates across all levels of experience and expertise - junior through senior level AI Product Engineers.

Responsibilities:

Client Advisory & Product Vision

Partner directly with Financial Services clients to identify, prioritize, and shape Agentic AI use cases across customer operations, underwriting, claims, risk, compliance, finance, and technology.

Lead client workshops to define agent personas, responsibilities, autonomy boundaries, human-in-the-loop checkpoints, and escalation logic.

Translate evolving business needs into agentic product backlogs, roadmaps, and MVP definitions.

Support executive conversations around GenAI platform strategy, operating models, vendor selection, and scale-out approaches.

Agentic Platform & Architecture Design

Design and implement multi-agent architectures using modern GenAI tooling, including:

Planner, executor, reviewer/critic, and supervisor agents

Tool-calling and function-calling agents

Memory-enabled agents (conversation, semantic, episodic, and structured memory)

Leverage LangChain and LangGraph for agent orchestration, workflows, and control flow.

Apply DSPy and declarative prompt optimization techniques for repeatability, performance tuning, and regression control.

Design agent interaction patterns such as hierarchical agents, collaborating agents, and event-driven agent workflows.

Define standardized agent contracts, interfaces, and schemas to enable reuse and scale.

Agentic SDLC & Engineering Delivery

Own delivery across the full Software Development Lifecycle (SDLC), extending it into a formal Agentic SDLC, including:

Agent design specifications and behavior contracts

Prompt, policy, and tool versioning

Simulation environments and offline evaluation

Automated testing of agent flows and guardrails

Controlled rollout, telemetry-driven optimization, and continuous learning

Build production-grade AI services primarily using Python, integrating:

LLM providers such as Anthropic (Claude), OpenAI, and open-source models

Retrieval-Augmented Generation (RAG) using vector databases (e.g., Pinecone, FAISS, Milvus, Weaviate)

Implement CI/CD pipelines for agent code, prompts, and policies.

Integrate GenAI agents with client systems via APIs, workflow engines, event streams, and data platforms.

Observability, Evaluation & Optimization

Implement agent observability including tracing, decision logging, tool usage, and failure analysis.

Apply evaluation frameworks for hallucination detection, consistency checks, and fitness scoring.

Design feedback loops incorporating human-in-the-loop review and reinforcement.

Monitor cost, latency, throughput, and behavioral drift across deployed agents.

Governance, Risk & Financial Services Compliance

Design Agentic AI platforms aligned with Financial Services regulatory expectations, including:

Auditability and traceability of agent decisions

Model and prompt explainability

Data privacy and security controls

Resilience and fail-safe mechanisms

Embed guardrails and policies addressing hallucination risk, bias, unauthorized actions, and escalation failures.

Produce documentation supporting risk, compliance, internal audit, and regulator engagement.

Team Leadership & Firm Contribution

Provide technical leadership and mentorship to consulting delivery teams.

Contribute to internal GenAI accelerators, agent frameworks, and reusable assets.

Support RFPs, proposals, and client solution designs with credible GenAI and agentic architectures.

Participate in thought leadership on Agentic SDLC, GenAI engineering, and responsible autonomy.

Benefits

This position comes with competitive compensation and benefits package:

Competitive salary and performance-based bonuses

Comprehensive benefits package

Career development and training opportunities

Flexible work arrangements (remote and/or office-based)

Dynamic and inclusive work culture within a globally known group

Private Health Insurance

Retirement Benefits

Paid Time Off

Training & Development

XML job scraping automation by YubHub

As a Software Engineer, Services Platform at Cursor, you'll build the platform-level primitives that make it hard for product teams to build brittle systems and easy to build resilient ones.

Cursor is scaling fast, hundreds of engineers shipping to millions of developers, and your core focus will be the abstractions that make that sustainable: service provisioning, deploy tooling, workflow orchestration, and defining what it means to own and operate a service at Cursor. You'll work at the intersection of developer experience and production reliability, building the golden pathways that every engineering team runs on.

Example projects include...

• Establishing durable workflow orchestration as a first-class platform: defining best practices, building shared abstractions, and creating the standard that every team uses for reliable, long-running workflows.

• Designing a declarative service configuration framework that makes it trivial to provision, deploy, and operate new services, so spinning up a new backend goes from days to minutes.

• Defining the contract for service ownership: what it means to own a service, how services integrate with Cursor's infrastructure abstractions, and building the service catalogue so incidents get resolved in minutes, not hours.

You may be a fit if

• You have experience building internal developer platforms, service frameworks, or infrastructure abstractions that other engineers depend on.

• You've worked extensively with Temporal, durable workflow engines, or similar orchestration systems and have strong opinions on best practices.

• You care deeply about developer experience. You think about how other engineers interact with your systems and design for simplicity and correctness by default.

• You have experience with deployment tooling, CI/CD pipelines, or service mesh architectures.

• You understand the tradeoffs in microservice vs. monolith architectures and can help teams navigate service decomposition pragmatically.

• You have strong software engineering fundamentals and enjoy shipping production systems that make the entire organization more productive.

XML job scraping automation by YubHub

We are seeking an experienced and innovative AI Product Engineer – Agentic Platforms to join our Financial Services Artificial Intelligence & Business Lines (FS-ABL) practice. This role is ideal for a consulting technologist with deep expertise in modern GenAI tooling, agentic system design, and enterprise SDLC, who can partner directly with clients to envision, design, develop, and deploy Agentic AI platforms in regulated environments.

In this role, you will work at the intersection of client advisory, AI product engineering, and delivery execution, helping banks, insurers, and capital markets firms transition from GenAI pilots to production-grade, governed, multi-agent systems. You will apply leading GenAI frameworks and LLM platforms , including Anthropic, OpenAI, LangChain, LangGraph, DSPy, and vector databases,while operating across the full Agentic SDLC.

P&C Insurance knowledge and experience is a significant plus. Additionally, familiarity with core insurance platforms like Guidewire, DuckCreek or Majesco will be extremely helpful to succeed in this role.

We are looking for candidates across all levels of experience and expertise - junior through senior level AI Product Engineers.

Responsibilities:

Client Advisory & Product Vision

Partner directly with Financial Services clients to identify, prioritize, and shape Agentic AI use cases across customer operations, underwriting, claims, risk, compliance, finance, and technology.

Lead client workshops to define agent personas, responsibilities, autonomy boundaries, human-in-the-loop checkpoints, and escalation logic.

Translate evolving business needs into agentic product backlogs, roadmaps, and MVP definitions.

Support executive conversations around GenAI platform strategy, operating models, vendor selection, and scale-out approaches.

Agentic Platform & Architecture Design

Design and implement multi-agent architectures using modern GenAI tooling, including:

Planner, executor, reviewer/critic, and supervisor agents

Tool-calling and function-calling agents

Memory-enabled agents (conversation, semantic, episodic, and structured memory)

Leverage LangChain and LangGraph for agent orchestration, workflows, and control flow.

Apply DSPy and declarative prompt optimization techniques for repeatability, performance tuning, and regression control.

Design agent interaction patterns such as hierarchical agents, collaborating agents, and event-driven agent workflows.

Define standardized agent contracts, interfaces, and schemas to enable reuse and scale.

Agentic SDLC & Engineering Delivery

Own delivery across the full Software Development Lifecycle (SDLC), extending it into a formal Agentic SDLC, including:

Agent design specifications and behavior contracts

Prompt, policy, and tool versioning

Simulation environments and offline evaluation

Automated testing of agent flows and guardrails

Controlled rollout, telemetry-driven optimization, and continuous learning

Build production-grade AI services primarily using Python, integrating:

LLM providers such as Anthropic (Claude), OpenAI, and open-source models

Retrieval-Augmented Generation (RAG) using vector databases (e.g., Pinecone, FAISS, Milvus, Weaviate)

Implement CI/CD pipelines for agent code, prompts, and policies.

Integrate GenAI agents with client systems via APIs, workflow engines, event streams, and data platforms.

Observability, Evaluation & Optimization

Implement agent observability including tracing, decision logging, tool usage, and failure analysis.

Apply evaluation frameworks for hallucination detection, consistency checks, and fitness scoring.

Design feedback loops incorporating human-in-the-loop review and reinforcement.

Monitor cost, latency, throughput, and behavioral drift across deployed agents.

Governance, Risk & Financial Services Compliance

Design Agentic AI platforms aligned with Financial Services regulatory expectations, including:

Auditability and traceability of agent decisions

Model and prompt explainability

Data privacy and security controls

Resilience and fail-safe mechanisms

Embed guardrails and policies addressing hallucination risk, bias, unauthorized actions, and escalation failures.

Produce documentation supporting risk, compliance, internal audit, and regulator engagement.

Team Leadership & Firm Contribution

Provide technical leadership and mentorship to consulting delivery teams.

Contribute to internal GenAI accelerators, agent frameworks, and reusable assets.

Support RFPs, proposals, and client solution designs with credible GenAI and agentic architectures.

Participate in thought leadership on Agentic SDLC, GenAI engineering, and responsible autonomy.

Benefits

This position comes with competitive compensation and benefits package:

Competitive salary and performance-based bonuses

Comprehensive benefits package

Career development and training opportunities

Flexible work arrangements (remote and/or office-based)

Dynamic and inclusive work culture within a globally known group

Private Health Insurance

Retirement Benefits

Paid Time Off

Training & Development

Industry: Technology

Category: Engineering

Salary Range: Competitive salary and performance-based bonuses

Salary Min: 95000

Salary Max: 150000

Salary Currency: USD

Salary Period: year

Required Skills:

Generative AI

Agentic AI

Agent-based systems

Multi-agent architectures

LLM platforms

Vector databases

Python

CI/CD pipelines

APIs

Workflow engines

Event streams

Data platforms

Observability

Evaluation frameworks

Human-in-the-loop review

Reinforcement learning

Governance

Risk management

Financial Services compliance

Team leadership

Mentorship

Thought leadership

Preferred Skills:

Cloud computing

Containerization

DevOps

Machine learning

Natural language processing

Recommendation systems

deployed agents

XML job scraping automation by YubHub

You will work closely with the Tech Lead to build the "Hybrid Model" ecosystem, integrating a best-in-class 3rd party Email Service Provider (ESP) with Future’s internal powerhouses: Alchemy (delivery), SCV (Single Customer View), and Advisor (AI).

Your primary focus will be building the robust integration layers, data pipelines, and internal tools that allow our marketing teams to orchestrate hyper-personalised campaigns at scale.

Key Responsibilities

• Integration Development: Build and maintain secure, high-performance APIs and connectors that sync data between our internal SCV (Single Customer View) and the external ESP (Email Service Provider).
• Internal Tools: Build user interfaces and "Control Tower" features (within Cerebrum) that allow non-technical marketing teams to define segments, trigger journeys, and view performance dashboards.
• Template Engineering: Work with the Iris templating system to ensure it can dynamically render personalised content blocks served by our AI Advisor engine.
• Full Stack Implementation: Write clean, maintainable code across the stack (backend APIs, database queries, frontend dashboards), ensuring high test coverage and documentation.
• Collaboration: Partner with the AI Engineer to implement personalisation logic and working with the Tech Lead to ensure architectural alignment.
• Migration Support: Assist in the technical migration of legacy campaigns and data from old providers (Selligent, Mailchimp) to the new unified platform.

Experience that will put you ahead of the curve...

• Full Stack Proficiency: Strong experience in modern web development, specifically with PHP (Symfony/Laravel) or Node.js/Golang for backend services, and React/TypeScript for frontend tools.
• API Integration: Significant experience consuming and building RESTful or GraphQL APIs, specifically integrating with third-party SaaS platforms (e.g., Salesforce, Stripe, or ESPs).
• Database Skills: proficiency with SQL (MySQL, PostgreSQL) and NoSQL databases, capable of writing efficient queries for large datasets.
• Event-Driven Architecture: Understanding of event-driven patterns (e.g., webhooks, queues, pub/sub) to handle real-time user actions like "abandoned cart" triggers.
• MarTech Awareness: Familiarity with marketing automation concepts (segments, journeys, triggers) or experience working with ESPs/CDPs is a big plus.
• DevOps Mindset: Experience with CI/CD pipelines, Docker, and cloud environments (AWS/GCP).
• Problem Solving: Ability to debug complex data flow issues across multiple distributed systems.
• Personal Automation: Proactively identifies opportunities to automate personal workflows and tasks, showcasing resourcefulness and a commitment to efficiency through the use of AI tools (e.g., Cursor, Windsurf, Copilot, Bolt).

Beneficial Skills & Experience

• Marketing APIs: Specific experience with the APIs of major ESPs like Salesforce Marketing Cloud, Braze, or Mailchimp.
• Data Engineering: Basic knowledge of ETL processes or data warehousing (BigQuery).
• Workflow Engines: Experience with Temporal.io or similar tools for managing complex business logic.
• Testing: Strong belief in automated testing (Unit, Integration, E2E)

What's in it for you

The expected range for this role is £40,000 - £55,000

This is a UK Remote role.

… Plus more great perks, which include;

• Uncapped leave, because we trust you to manage your workload and time
• When we hit our targets, enjoy a share of our profits with a bonus
• Refer a friend and get rewarded when they join Future
• Well-being support with access to our Colleague Assistant Programmes
• Opportunity to purchase shares in Future, with our Share Incentive Plan

XML job scraping automation by YubHub

As a Senior Backend Engineer, you will own major backend systems for frontier agentic data products, driving projects from early exploration through production deployment. You will build scalable services and pipelines that support agent workflows, architect modular, reusable backend systems, and operate in high-ambiguity environments.

Key responsibilities include:

• Designing and building scalable systems while partnering closely with research, product, operations, and other engineering teams
• Building scalable services and pipelines that support agent workflows
• Architecting modular, reusable backend systems that adapt to evolving product needs
• Operating in high-ambiguity environments and breaking down open-ended problems
• Partnering cross-functionally with product, research/ML, and infrastructure teams

Ideal experience includes 5+ years of full-time software engineering experience, strong backend engineering fundamentals, and experience building systems that scale.

Compensation packages at Scale include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors.

Additional benefits include comprehensive health, dental, and vision coverage, retirement benefits, a learning and development stipend, and generous PTO.

XML job scraping automation by YubHub

The nature of our business means you'll spend significant time helping customers who've already adopted Temporal unlock more value by expanding into additional use cases, teams, and workloads. This is a high-velocity, technically deep role.

You'll partner with developers, architects, and engineering leaders at fast-moving companies to help them understand how Temporal fits into their existing architecture and prove out value through hands-on technical work.

You'll be working in a consumption model where usage grows over time, which means building strong technical relationships and staying engaged with accounts as they scale.

As an early member of a growing team, you should be comfortable with ambiguity, frequent context switching, and creating leverage through reusable assets that help the broader team move faster.

Must reside in San Francisco, CA

XML job scraping automation by YubHub

Solve distributed systems problems: Own session management across scaled-out workers , including affinity, checkpointing, crash recovery, and consistency under concurrent access.

Build a function execution platform: Own a serverless-style runtime where customers deploy custom logic , build orchestration, container lifecycle, autoscaling, and versioned rollouts.

Own developer experience and test infrastructure: Build CLI tools, local development environments, and test execution frameworks that let engineers iterate quickly and ship with confidence.

Raise the bar on production quality: Drive observability, incident response, and engineering best practices across the team.

We're looking for a senior software engineer with 5+ years of experience in infrastructure, platform, or systems work. You should have strong Python and Go skills, as well as a deep understanding of distributed systems, consistency, fault tolerance, state management, and concurrency.

Experience with Kubernetes and cloud-native infrastructure is also required. You should be able to build developer-facing tooling, such as CLIs, SDKs, local dev environments, or internal platforms.

A high bar for code quality, thorough testing, thoughtful code review, and sustainable engineering practices are essential. You should be comfortable operating what you build, on-call, incident response, and production ownership.

AI-native workflow is a must, and you should actively use LLMs and AI-assisted tools in your daily development.

XML job scraping automation by YubHub

A significant portion of backend logic is shared across services, and this role will help define, maintain, and scale that foundation.

You will own and improve internal schema and code generation tooling that ensures consistency and correctness across services.

You will work on and extend our custom job scheduler, improving reliability, observability, and execution guarantees for distributed workloads.

You will contribute to safely execute large-scale concurrent and distributed operations.

You will play a key role in defining and maintaining API standards across teams, ensuring performance, backward compatibility, and clear evolution strategies.

You will collaborate closely with Product and various Engineering teams to design systems that are reliable, scalable, and maintainable over time.

The Core Systems team is responsible for the foundational backend infrastructure that powers Weights & Biases within CoreWeave.

Much of the platform's critical logic is shared across services, and this role sits at the center of that foundation.

You will work on the systems that other engineers build upon , from execution frameworks and schedulers to schema tooling and API standards.

This is a high-leverage role focused on durability, scalability, and long-term maintainability.

The systems you design and evolve will directly impact reliability, developer velocity, and the ability of the platform to scale with growing workloads.

You'll collaborate across teams to ensure that shared backend abstractions remain clean, performant, and consistent as we continue to expand our adoption of technologies like GraphQL and gRPC.

If you enjoy owning deep technical infrastructure, shaping engineering standards, and building systems that other engineers depend on every day, this role offers meaningful scope and impact.

You will be surrounded by some of the best talent in the industry, who will want to learn from you, too.

Come join us!

XML job scraping automation by YubHub

As a Staff Engineer, you'll lead initiatives that span front-end and back-end services , delivering performant, secure, and scalable features. You'll help define architecture, drive implementation, and collaborate closely with Design, PM, and Platform teams. You'll also work directly with our technical architects to help shape what we build , and how we build it.

This is a high-impact role in a growing, strategic product area with strong executive visibility.

Role Details:

• Design, build, and maintain end-to-end features using modern JavaScript and cloud-native technologies (React, Node.js, TypeScript, PostgreSQL).
• Lead technical design for key initiatives, driving quality, scalability, and maintainability.
• Build reusable and performant UI components for a best-in-class no-code builder experience.
• Own services throughout their lifecycle , including implementation, testing, deployment, observability, and incident response.
• Work closely with Product, Design, and Architecture to define the “what” and “how” of features, ensuring solutions are both user-friendly and technically sound.
• Partner with infrastructure and platform teams to optimize system performance and reliability
• Mentor and support engineers across the team, fostering a culture of quality, ownership, and continuous improvement.
• Contribute to cross-functional planning, architectural reviews, and team-wide engineering practices.

Experience:

• 6+ years of experience building modern web applications in a full-stack environment.
• Deep expertise in TypeScript, ReactJS, and Node.js (Express or similar frameworks).
• Experience designing APIs, working with relational databases (PostgreSQL or similar), and building services in a distributed, cloud-based architecture.
• A strong product mindset , you work well with Product and Design and care about delivering intuitive and elegant user experiences.
• Ability to collaborate closely with Architects to make smart technical tradeoffs, and drive alignment across teams.
• Passion for craftsmanship and high engineering standards (testing, monitoring, documentation, scalability).
• Excellent communication skills, with the ability to lead technical discussions and build consensus across functions.
• A growth mindset and interest in mentoring others and upleveling the team.

Nice to Haves:

• Experience with PostgreSQL, Docker, and Kubernetes.
• Exposure to low-code/no-code tools, workflow engines, or visual development platforms.
• Interest in AI-assisted developer tooling or automation.

Education and Training:

• Bachelor's in Computer Science, or relevant industry experience

XML job scraping automation by YubHub

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.

Okta is scaling internal AI and automation across the company,from employee productivity to building differentiated AI-native products. To make that scale real, we’re building platforms that democratize agent and automation development: secure, reliable building blocks that let teams ship AI-powered workflows faster, safely, and with confidence.

As a Staff Product Manager, AI & Automation Platform, you’ll lead product strategy and execution for the platform layer that enables internal builders (engineers, automation developers, analysts, and power users) to create and run agents, automations, and integrations,while meeting Okta’s high bar for security, reliability, compliance, and operational rigor.

You’ll partner closely with your Bangalore Engineering POD and collaborate deeply with US-based product, security, and engineering stakeholders.

Key Responsibilities:

• Own the platform product strategy
• Define the vision, roadmap, and success metrics for an AI & Automation Platform that enables internal teams to build, test, deploy, and operate agents and automations at scale
• Identify the highest-leverage platform capabilities(e.g., orchestration, connectors, governance, observability) that reduce time-to-value for internal AI initiatives.
• Translate company priorities into clear platform outcomes: adoption, reliability and security, developer velocity and cost efficiency

Nice to Have:

• Experience with enterprise identity/security patterns (e.g., SSO, provisioning, authorization models)
• Familiarity with integration platforms, workflow engines, or API ecosystems.
• Experience in building internal platforms in a large global company with strong compliance

XML job scraping automation by YubHub

The nature of software development has changed and Replit is at the forefront of that revolution. The product platform team builds and scales the primitives that Replit Agent uses to empower over 40 million users to build anything they want.

This role is ideal for a senior platform-minded web engineer who's shipped at scale, thrives in high-ownership environments, and can define what “good” looks like across reliability, performance, and developer experience.

We've hit a significant scale and have escape velocity. A number of our systems need to be scaled and rebuilt, so you'll get to build these out for 0 → 1 → huge scale quickly.

You'll work closely with product other engineers, platform engineers, designers, product managers, and go-to-market partners to deliver foundational capabilities that unlock entire categories of product development.

This is why we require product engineers with a strong product sense and past distributed systems experience that are excited about building at scale platform primitives!

Responsibilities

• Lead major cross-team platform initiatives, taking foundational systems from 0 → 1 and scaling them to support millions of users
• Build shared, extensible Agent primitives that Replit Agent can reuse safely and consistently (Meta Programming)
• Identify the highest-leverage technical bottlenecks (performance, reliability, correctness, abuse, observability), then design and ship solutions for our scale
• Raise the bar for engineering excellence through architecture reviews, code quality, reliability standards, and mentorship
• Partner across teams to improve platform adoption, ergonomics, and velocity — turning platform work into measurable outcomes

Core areas you'll work on

• Agents and Replit users depend on us to build applications (e.g. Connectors framework, Content/configuration primitives (CMS + product surfaces), Data/analytics/events + experimentation primitives)
• Replit Agent as a principal in third party systems. Agent can be fully used within ChatGPT and publishes straight to the iOS app store. We’ll be doing loads of that.
• Platform product teams rely on us to ship consistently (e.g. Identity & Access platform (SSO/SCIM), Localization/i18n platform, Notifications & communications platform)
• Core web platform infrastructure (e.g. performance & page load optimization, observability and debugging workflows, caching strategy and reliability)

Requirements

• 5+ years of professional software engineering experience
• Understanding of the full agentic software development stack, helping coding agents build, test and review correct code
• Strong track record leading complex projects with cross-functional stakeholders
• Experience building and operating platform systems that other teams depend on
• Experience operating and scaling systems in production (reliability, performance, incidents, on-call readiness)
• Strong product judgment: you can balance UX, speed, correctness, and long-term maintainability
• Comfort working in modern web stacks such as TypeScript, React, Node.js, Postgres

Bonus points

• Experience working in environments with a high engineering bar (or a fast-growing startup where you shipped fast _without_ burning out quality)
• Experience with platform and distributed systems patterns (queues, workflows, caching, rate limiting, async processing)
• Familiarity with systems like Redis, Postgres, Workflow engines (e.g. Temporal), Auth and enterprise identity (SSO, SCIM), Abuse protection and edge systems (Cloudflare), Cloud platforms (GCP), Observability (Datadog, Sentry), Localization, Experimentation and event pipelines (Statsig, Segment, analytics/event tracking)
• Excited about the future of programming, including agent workflows and developer tools
• Exposure to agent ecosystems (e.g. MCP-style patterns, tool integrations, structured automation)

Example Projects You’ll Work On

• Connectors platform for agents — ship a secure connector framework (OAuth/permissions/data access) so agents can integrate with Slack/Notion/GitHub/etc.
• Agent-facing external surfaces — own high-quality embedded experiences (desktop/extension/embeds) that let agents act in-context across tools
• Safety + abuse controls for agent actions — design permissioning, rate limits, and policy enforcement so agents can operate safely at scale
• Real-time notifications platform — design in-app/email surfaces + build reliable delivery/fanout, preferences, and observability
• Core web platform performance + caching — improve latency and reliability via caching strategy (Redis), profiling, and safe fallbacks
• Events + experimentation primitives — standardize tracking/metrics + feature flags/rollouts so teams can ship safely and measure impact

XML job scraping automation by YubHub