Staff Product Engineer, Enterprise AI
Mozilla · Software
staffRemote
Salary Range (USD)
$185k - $220k
Location
USA or Canada
Visa Support
Not mentioned
Funding Stage
Unknown
Job Responsibilities
- • Own features end‑to‑end from concept through launch, adoption, and iteration
- • Work full‑stack on AI‑powered chat, search, research, workflow automation, admin, and integrations
Required Skills
10+ years engineering experience at staff scopeHands‑on AI product work with LLMs, RAG, agents, retrieval, model/provider abstractionComfort with ambiguity and evolving architecture and enterprise requirementsMust reside in and have work authorization for the US or CanadaNo visa sponsorship
Engineering Culture & Tech Stack
ownership
ambiguous environment
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Mozilla / Thunderbird / Thunderbolt | Staff Product Engineer, Enterprise AI | REMOTE (US or Canada) | Full-Time | $185K–$220K USD / $155K–$185K CAD | https://grnh.se/viz7vum71us
We're building Thunderbolt (https://github.com/thunderbird/thunderbolt). We're an 8-person and growing team within the ~60-person company behind Thunderbird, the open-source email client used by 20M+ people.
Thunderbolt is an open-source, cross-platform AI product built on the principle that people and organizations should be in control of their data, infrastructure, and model choices. It's moving from early development into enterprise use cases, and we need someone to own features end to end — concept through launch, adoption, and iteration — not just close tickets.
You'd work full-stack on AI-powered chat, search, research, workflow automation, admin, and integrations. We're looking for 10+ years of engineering experience at Staff scope, hands-on AI product work (LLMs, RAG, agents, retrieval, model/provider abstraction), and comfort in ambiguity — architecture and enterprise requirements are still being defined. Bonus: self-hosted or regulated deployments, EU AI Act / GDPR / SOC 2 familiarity.
Must reside in and have work authorization for the US or Canada. No sponsorship. We read every cover letter - please make it authentic.
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Content parsed by LLM from Hacker News raw data. Confidence:MEDIUM