Senior Engineering Manager, Enterprise AI Product
New
J
JobgetherEnterprise AI
Based in the United States, globally distributed teamFull-TimeManager
Salary$215,000–$240,000 USD
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Job Details
- Experience
- 15+ years of professional software development experience; 5+ years of experience managing engineering teams
- Required Skills
- Artificial IntelligenceCI/CDLLM
Requirements
- 15+ years of professional software development experience, including significant experience in senior engineering leadership or complex product delivery.
- 5+ years of experience managing engineering teams, including senior engineers or senior individual contributors.
- Proven track record of leading teams that have delivered polished, high-quality products with strong standards for engineering and user experience.
- Strong ability to turn ambiguous product and technical direction into clear plans, ownership structures, priorities, and sustainable delivery momentum.
- Technical fluency across AI-enabled products, including LLM applications, RAG workflows, agents, enterprise search, automation, on-device AI, or AI evaluation.
- Experience delivering complex user-facing applications across multiple platforms using technologies such as Tauri, Electron, or React Native.
- Experience with enterprise software, regulated environments, or complex products involving security, privacy, compliance, and customer-controlled deployment.
- Practical experience with local-first, offline-capable, self-hosted, hybrid, or on-premise architectures.
- Experience improving engineering operating practices covering technical planning, code review, release management, testing, and CI/CD.
- Excellent communication skills with the ability to articulate technical priorities, release risks, and architectural tradeoffs.
- Strong people leadership, mentoring, hiring, and cross-functional collaboration skills.
- Experience working effectively with globally distributed teams.
Responsibilities
- Lead engineering execution by establishing priorities, ownership, timelines, dependencies, quality expectations, and delivery plans for a growing AI product.
- Manage and develop a team of senior engineers and contractors through coaching, feedback, performance management, hiring, onboarding, and career development.
- Stay technically engaged by contributing code when appropriate, reviewing technical work, evaluating architectural tradeoffs, and helping the team maintain engineering momentum.
- Partner with product and technical leadership to translate product strategy, AI capabilities, user experience goals, and technical priorities into coordinated engineering roadmaps.
- Establish lightweight but effective planning, review, release, and follow-through processes that improve predictability without slowing innovation.
- Maintain high standards for code quality, testing, documentation, reliability, security, maintainability, and production readiness.
- Guide engineering decisions across local-first, offline-capable, self-hosted, hybrid, on-premise, and other privacy-focused architectures.
- Improve engineering practices around technical planning, code review, release readiness, testing, CI/CD, documentation, technical debt, and maintainability.
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