AVP, Lead AI Engineer

OVERVIEW
Drive AI engineering workstreams across the Audit+ program, ensuring compliance of UW and Claims processing, automation of controls, as well as driving cost reduction.

ROLE
This role will work closely with regional teams to identify and build production grade foundational capabilities, platform those capabilities to enable rapid operationalization and scale out of Audit+ AI capabilities. The primary focus is on end-to-end automation of controls across Claims, UW, Finance and Technology.

FOCUS AREAS & RESPONSIBILITIES
• Develop the next generation of AI driven Audit+ platforms and AI assets, including Agentic framework 
• Build scalable pipelines for data ingestion, feature engineering, model training, evaluation, and monitoring
• Develop and integrate generative AI applications, including LLM-based workflows, agents, and retrieval-augmented generation (RAG) solutions
• Ensure solutions meet security, privacy, compliance, and responsible AI standards
• Optimize model performance, reliability, latency, and cost across the AI lifecycle
• Platform capabilities for extending AI enablement to human-lead operations in areas like QA, Training | Operations for faster and efficient production and introduce efficiencies in distribution workflows 
• Enable sales analytics | marketing with a foundational layer of AI with Consumer LLM as needed
• Drive implementation and change management in collaboration with regional D&A leads, business and technology partners
• Work with the Consumer+ Platform Engineering team to develop reusable Foundational AI Assets | Applications to accelerate local deployments 
• Support Business Development by evangelizing our AI success stories to stakeholders and sponsors as needed
• Enable the regional and local teams to leverage Global Consumer+ platforms and be self-sufficient

Operating Network: 
• Work closely with regional Data & Analytics teams to identify opportunities and assist in implementation  
• Collaborate with Regional IT, GDO, Global Analytics, Ops for data | infra | integration related to implementation
• Collaborate with teams to enforce responsible AI, model risk management, and AI governance