Build, lead, and develop a team of Analytics Engineers
Set clear goals, provide ongoing coaching and feedback
Recruit and retain top-tier analytics engineering talent
Define and own the multi-year roadmap for the Applied Analytics function
Establish the team's technical standards, architectural patterns, and governance frameworks
Drive the adoption of agentic AI workflows
Own the strategic direction for conversational AI capabilities
Guide the team in designing and delivering RAG pipelines
Set the architectural vision for agent design
Champion responsible AI practices
Lead the strategy and governance for AI-driven BI across insurance lines of business
Drive the team's use of dimensional modeling and BI best practices
Lead the delivery of GenAI capabilities supporting regulatory filing automation
Ensure the team embeds domain taxonomies into solution design
Partner closely with Legal and Compliance to meet evolving standards.
Oversee the engineering and maintenance of domain-specific knowledge bases
Lead the team through the full AI solution lifecycle
Establish and enforce GitHub best practices for version control.
Drive standardization of experiment tracking and model registries.

8+ years of relevant experience in analytics engineering, data science, or AI/ML
Demonstrated experience building and developing high-performing teams in an Agile environment
Proven track record delivering production AI/ML solutions
Strong understanding of BI principles
Experience designing and executing a multi-year technical roadmap
Proficiency in Python and SQL
Experience with cloud platforms (GCP Vertex AI, AWS SageMaker/Bedrock, or Azure AI Services)
Strong familiarity with MLOps practices
Experience with responsible AI principles
Bachelor's degree in Computer Science, Data Science, Engineering, Applied Mathematics, or a related analytical field
Candidate must be authorized to work in the US without company sponsorship.

Director of Applied Engineering

Key skills