AI Engineering Manager
Skills
- Proficiency with Python and ML frameworks (PyTorch or TensorFlow)
- Hands-on experience with Databricks, Mosaic AI Gateway, and Databricks stack
- Experience with language models, embeddings, RAG, agents and agentic workflows
- Strong cloud and distributed systems architecture knowledge
- Solid software engineering practices: testing, code review, CI/CD, test automation
- Experience designing systems for medium-to-large scale data (10s–100s TB)
- Excellent leadership, communication, and stakeholder management skills
Responsibilities
- Manage, coach, and scale multiple distributed engineering teams (software, data, AI) to meet roadmap and quality objectives
- Drive deployment and operationalization of state-of-the-art AI models and agentic systems (LLMs, RAG, SQL/Agents, MCP)
- Collaborate with product, QA, and cross-functional partners to deliver end-to-end AI solutions
- Influence architecture, participate in design discussions, and ensure consistency across platforms
- Operate with strong incident, configuration, and escalation management practices
- Partner with VP/CTO on strategy, roadmap planning, and engineering scalability toward 50+ engineers
- Recruit, run performance reviews, mentor engineers, and develop team career paths
Education
- Bachelor's degree in Computer Science, Engineering, or related field (required)
- Advanced degree (MS/PhD) in ML/AI or related field preferred
Benefits
- Competitive salary and equity
- Comprehensive health, dental, and vision benefits
- 401(k) retirement plan
- Generous paid time off and flexible remote work
- Professional development and learning allowance
- Inclusive, mission-driven culture focused on impact
Average salary estimate
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