Staff Product Engineer (Enterprise AI)
- Source: Greenhouse
- Mozilla
- $185,000 to $220,000 /yr
- On-site
- New York City
- Full-Time
- Staff
Job Description
- Thunderbolt is an open-source, cross-platform AI product initiative from the team behind Thunderbird. It is being built around a clear principle: people and organizations should be able to use AI while staying in control of their data, infrastructure, model choices, and long-term options
- Thunderbolt is designed to support flexible deployment models, integrations with AI tools and workflows, and use cases across desktop, web, and mobile
- We’re looking for a Staff Product Engineer to help build Thunderbolt as it moves from early product development into enterprise use cases
- This role sits at the intersection of full-stack product engineering, AI-enabled product development, enterprise workflows, technical execution, product judgment, and post-launch iteration
- You’ll work across the stack to turn product direction, user needs, partner feedback, and enterprise requirements into complete product features for AI-powered chat, search, research, workflow automation, administration, integrations, and enterprise workflows
- This is not a role focused only on implementing tickets. You’ll own product work from concept through launch, adoption, and iteration, helping the team understand whether features are usable, reliable, being used, and creating value
- Strong candidates will be able to turn ambiguous product ideas and technical direction into shipped product experiences, reusable product and engineering patterns, and practical improvements that help Thunderbolt scale as both an open-source product and an enterprise-ready platform
- Own the implementation of Thunderbolt product features from concept through launch, adoption, and iteration
- Translate product vision, user needs, partner feedback, and enterprise requirements into practical technical plans and shipped product experiences
- Work across the stack to build, integrate, test, and ship complete product features
- Build features for AI-powered chat, search, research, workflow automation, administration, integrations, and enterprise workflows
- Partner closely with product, design, engineering, enterprise-facing teams, and open-source contributors to clarify requirements and deliver high-quality outcomes
- Collaborate with senior technical leadership to turn product-shaping technical direction into executable product work
- Use AI-assisted development tools thoughtfully to accelerate implementation while maintaining strong judgment around quality, security, maintainability, and reliability
- Make thoughtful technical and product tradeoffs in ambiguous situations, balancing speed, usability, maintainability, reliability, and enterprise needs
- Follow through after launch by reviewing usage, qualitative feedback, support signals, quality issues, and adoption patterns
- Instrument features or collaborate on measurement approaches that help the team understand adoption, reliability, and product value
- Identify product gaps, technical risks, edge cases, and opportunities to improve the user experience
- Write clear, maintainable, well-tested code across front-end, back-end, APIs, integrations, and infrastructure-adjacent areas
- Help establish reusable product and engineering patterns that allow future features to be built more efficiently
- Contribute to a product engineering culture grounded in ownership, quality, experimentation, user value, and practical execution
- What success looks like:
- In this role, success means helping Thunderbolt turn ambiguous product ideas, technical direction, user needs, and enterprise requirements into complete product capabilities that are usable, reliable, maintainable, and valuable
- You will help the team move quickly while also building the patterns, feedback loops, and product quality needed for Thunderbolt to scale as both an open-source product and an enterprise-ready platform
- Over time, successful work in this role will lead to:
- Shipped features that solve real user, partner, and enterprise needs
- Stronger full-stack product capabilities across AI-powered chat, search, research, workflow automation, administration, integrations, and enterprise workflows
- Clearer technical plans that translate product direction and enterprise requirements into executable work
- Better post-launch understanding of whether features are being used, working as intended, and creating value
- More reusable product and engineering patterns that help future features move faster
- Fewer product gaps, edge cases, and technical risks discov…
Skills
- platformai
- greenhouse
