AI Engineering Manager

Job Summary

Leading a team of 3-5 engineers, the full-time AI Engineering Manager will manage the development of agentic workflows and solutions on Databricks, ensuring high-quality production systems while coding alongside the team in a hybrid work environment.

Key responsibilities

• Hire, manage, and develop a team of embedded engineers, conducting regular 1:1s and career development activities
• Build and maintain the agentic harness, integrating tools for code quality checks and artifact generation
• Develop production templates and solutions on Databricks, ensuring operational readiness and monitoring

Required qualifications

• 2+ years of experience managing engineering teams, particularly in embedded or distributed environments
• Proven track record of shipping end-to-end systems to production with real users and SLAs
• 2+ years of hands-on experience with Databricks, including Delta Lake and MLflow
• Experience with Anthropic Claude and building developer tools using LLMs
• Strong proficiency in production-grade Python and SQL, along with CI/CD and API design skills