Senior Engineering Manager, Enterprise AI Product
New
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MZLAAI Product Software
Location: Remote Canada, Work across time zonesFull-TimeManager
Salary$190,000 - $220,000 CAD
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Job Details
- Experience
- 15+ years of professional software development experience
- Required Skills
- Artificial IntelligenceReact NativeCI/CDLLM
Requirements
- 15+ years of professional software development experience.
- 5+ years of experience managing technical teams, including senior engineers or senior individual contributors.
- Track record of leading a team that shipped polished, top-tier products.
- Ability to translate ambiguous product and technical direction into clear plans and delivery momentum.
- Technical fluency with AI-enabled products (LLMs, RAG workflows, agents, enterprise search, automation, on-device AI).
- Experience delivering complex applications across desktop, web, and mobile (e.g., Tauri, Electron, React Native).
- Experience with enterprise software in regulated environments (security, privacy, compliance, integrations).
- Practical experience with local-first, offline-capable, or self-hosted product architectures.
- Experience improving engineering practices (CI/CD, technical planning, testing, code review).
- Excellent communication skills regarding technical prioritization, risk, and tradeoffs.
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.
- Lead hiring, onboarding, and resource planning as the Thunderbolt engineering team grows.
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