Senior Engineering Manager (AI Product, Thunderbolt)

Role Overview

Join Mozilla as a Senior Engineering Manager for Thunderbolt, an open-source AI product initiative. This is a hands-on technical management role leading engineering execution, people management, and operating practices as Thunderbolt evolves from R&D incubation to a mature, production-ready product.

Key Missions

• Lead engineering execution, people management, and operating practices for Thunderbolt’s transition to product maturity.
• Define and enforce production-ready standards by establishing strong practices for:
  • planning
  • reviews
  • releases
  • follow-through
• Manage a senior engineering team while staying close to the codebase and technical execution.
• Coordinate delivery across employees, contractors, and technical partners.

Responsibilities (What You’ll Do)

• Translate ambiguous product/technical direction into clear plans, ownership models, and delivery momentum.
• Communicate effectively around technical prioritization, release risk, quality expectations, and tradeoffs.
• Improve engineering practices across areas such as:
  • technical planning
  • code review
  • release readiness
  • testing
  • documentation
  • CI/CD
  • maintainability and technical debt management

Requirements

• Strong people management and product engineering judgment.
• Enough technical depth to evaluate work credibly, support architectural and implementation tradeoffs, and keep shipping with quality.
• Excellent technical communication focused on priorities, risk, ownership, and tradeoffs.
• 5+ years managing technical teams (including senior engineers).
• 15+ years professional software development, with significant senior leadership or complex product delivery experience.
• Experience delivering complex applications across multiple platforms (e.g., desktop, web, mobile) using frameworks such as:
  • Tauri, Electron, React Native (or comparable)
• Experience with enterprise/regulatory environments (security, privacy, compliance readiness, integrations, customer-controlled deployment models).
• Practical experience with customer-controlled architectures, including local-first/offline, self-hosted, hybrid/on-premise, and air-gapped models, including tradeoffs for storage, sync, privacy, reliability, and UX.
• Track record of leading teams that shipped polished, top-tier products with high craft standards.
• Technical fluency with AI-enabled products, including tradeoffs across areas like LLM apps, RAG, agents, enterprise search, automation, on-device AI, or AI evaluation.
• Experience in open-source or maintainer-style environments.
• Experience with compliance/security standards such as SOC 2, HIPAA, ISO 27001, or similar.
• Experience taking products from zero to one in startup/new initiative contexts.

Nice-to-Have / Implied Strengths

• Ability to define what “production-ready” means for a new open-source AI product.
• Experience operating in environments requiring strong documentation, quality gates, and predictable release processes.