# Staff Product Engineer, Enterprise AI

**Company:** [Mozilla](https://hotfix.jobs/companies/mozilla)
**Location:** Remote
**Role:** Fullstack Engineering
**Experience:** 10+ years
**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
**Posted:** 2026-09-02

> 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.

## Job Description

## 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.

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