Senior Engineering Manager, Enterprise AI Product

Mozilla

1d•CA$190,000 - CA$220,000•Remote

About The Position

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 are looking for a Senior Engineering Manager to lead engineering execution, people management, and operating practices for Thunderbolt as it moves from R&D incubation into a more mature product and enterprise development phase. This role will help the team define what production-ready means at this stage: stronger release discipline, clearer ownership, higher user-facing product quality, stronger engineering practices, and a more scalable operating model. This is a hands-on technical management role for a seasoned engineering leader who has helped early-stage products become reliable, production-ready, and enterprise-ready. You will manage and grow a small senior engineering team, stay close to code quality and technical execution, and partner closely with product and technical leadership to turn an open-source, privacy-respecting AI product into something organizations can deploy with confidence. We are looking for someone who has seen this stage before: a promising early product, a small senior team, real enterprise interest, incomplete process, and the need to move quickly without creating fragile systems or one-off customer work.

Requirements

15+ years of professional software development experience, including significant experience in senior engineering leadership or complex product delivery roles.
5+ years of experience managing technical teams, including senior engineers or senior individual contributors.
A track record of leading a team that shipped polished, top-tier products held to a genuine standard of craft.
Strong ability to translate ambiguous product and technical direction into clear plans, ownership models, and delivery momentum.
Technical fluency with AI-enabled products, including the ability to evaluate tradeoffs across areas such as LLM applications, RAG workflows, agents, enterprise search, automation, on-device AI, or AI evaluation.
Demonstrated experience delivering complex applications across multiple platforms, such as desktop, web, and mobile, using technologies such as Tauri, Electron, React Native, or comparable frameworks.
Experience with enterprise software, regulated environments, or similarly complex technical products, including security, privacy, compliance readiness, administration, integrations, and customer-controlled deployment models.
Practical experience with local-first, offline-capable, self-hosted, hybrid, on-premise, air-gapped, or other customer-controlled product architectures, including tradeoffs related to data storage, sync, privacy, reliability, and user experience.
Experience improving engineering practices related to technical planning, code review, release readiness, testing, documentation, CI/CD, maintainability, or technical debt management.
Excellent communication skills around technical prioritization, release risk, ownership, quality expectations, and tradeoffs.

Nice To Haves

Experience working in open-source or maintainer-style engineering environments.
Experience with compliance or security standards such as SOC 2, HIPAA, ISO 27001, or similar frameworks.
Experience helping take a product from zero to one in a startup or new product initiative.

Responsibilities

Lead engineering execution by clarifying priorities, ownership, timelines, risks, dependencies, and quality expectations.
Manage engineers and contractors, including coaching, feedback, prioritization, performance support, and team development.
Stay close to the codebase by contributing code, reviewing technical work, evaluating tradeoffs, and helping the team maintain momentum and quality.
Partner with technical and product leadership to turn product direction, AI strategy, user experience goals, and technical priorities into coordinated engineering plans.
Establish planning, review, release, and follow-through practices that improve predictability and reduce bottlenecks.
Maintain high standards for code quality, testing, documentation, reliability, security awareness, maintainability, and release readiness.
Build strong product and architectural context across AI-enabled workflows, integrations, local-first or customer-controlled architectures, and release requirements.
Partner across product, design, enterprise-facing teams, and technical leadership to balance speed, user experience, privacy, quality, enterprise readiness, and long-term sustainability.
Lead hiring, onboarding, and resource planning as the Thunderbolt engineering team grows.
Help Thunderbolt scale from an incubation-stage product into a reliable, enterprise-ready open-source AI product.