Staff Product Engineer, Enterprise AI

Build and own full-stack AI product capabilities for enterprise workflows, from product concept through launch and iteration. The role requires Staff-level engineering experience, strong product judgment, and practical expertise in AI application architecture, enterprise software, and open-source products.

About the job

Responsibilities

Own implementation of product features from concept through launch, adoption, and iteration.
Translate product vision, user needs, partner feedback, and enterprise requirements into technical plans and shipped experiences.
Build, integrate, test, and ship complete features across the stack.
Develop AI-powered chat, search, research, workflow automation, administration, integrations, and enterprise workflows.
Collaborate with product, design, engineering, enterprise-facing teams, technical leadership, and open-source contributors.
Use AI-assisted development tools while maintaining quality, security, maintainability, and reliability.
Make technical and product tradeoffs in ambiguous situations.
Review usage, feedback, support signals, quality issues, and adoption after launch.
Instrument features and improve measurement of adoption, reliability, and product value.
Identify product gaps, technical risks, edge cases, and user-experience improvements.
Write clear, maintainable, well-tested code across front end, back end, APIs, integrations, and infrastructure-adjacent areas.
Establish reusable product and engineering patterns.

Requirements

10+ years of professional software engineering experience, including significant Staff-level scope, leadership, and impact.
Strong full-stack engineering skills across user interfaces, APIs, services, integrations, data flows, and infrastructure-adjacent areas.
Experience owning complex product features through planning, implementation, launch, evaluation, and iteration.
Experience building AI-enabled products or features, with familiarity with LLMs, RAG, agents, model/provider abstraction, data connectors, retrieval systems, or AI application architecture.
Experience evaluating and using multiple AI tools, models, frameworks, or development harnesses.
Experience with open-source enterprise products, developer tools, infrastructure products, platform products, or technically complex enterprise software.
Strong product judgment and ability to turn user, partner, customer, and product feedback into technical plans.
Ability to operate independently in a fast-changing product environment.
Strong understanding of software quality, testing, maintainability, security, performance, reliability, and implementation tradeoffs.
Strong collaboration and communication skills.
Awareness of enterprise needs including privacy, security, administration, access control, compliance, deployment flexibility, supportability, and responsible AI.

Nice-to-haves

Experience with self-hosted, hybrid, customer-controlled, or regulated deployment environments.
Familiarity with the EU AI Act, Cyber Resilience Act, GDPR, HIPAA, SOC 2, or similar frameworks.
Experience with enterprise customers, public-sector organizations, systems integrators, technical partners, or customer-facing engineering teams.
Experience contributing to reusable product patterns, component libraries, technical frameworks, or shared engineering practices.
Experience with instrumentation, observability, experimentation, or approaches to understanding product adoption, reliability, and value.

Skills

Full-Stack Engineering, LLMs, RAG, AI Agents, Model Abstraction, Data Connectors, Retrieval Systems, Ai Application Architecture, APIs, Integrations, Infrastructure, Testing, Observability, GDPR, SOC 2