VP AI Engineering

We are seeking a bold, technically deep, and strategically minded engineering executive to lead our AI Engineering organization. As VP of AI Engineering, you will own the architecture, development, and operation of the platforms and systems that power AI-driven innovation across our health plan enterprise. This is a critical leadership role responsible for transforming how our organization leverages artificial intelligence from predictive models that improve member outcomes to automation that drives operational efficiency across claims, care management, and utilization review.

You will partner closely with the VP Of AI Factory to execute prioritized AI initiatives and ensure it meets the specification laid out by that organization.

You will serve as the senior engineering authority for all AI initiatives, working in close partnership with AI Factory leader, Product, AI Governance, Data Science, Clinical Operations, and executive leadership to deliver production‑grade AI systems that are scalable, compliant, and clinically sound. You will be accountable for engineering excellence, team growth, and measurable business impact.

AI Engineering Strategy & Vision

• In collaboration with the office of the CEO and VP Of AI Factory, execute on the multi‑year technical roadmap for AI engineering, aligned with the company's strategic goals across care delivery, cost management, and member experience.
• Serve as the senior engineering voice for AI at the executive level, partnering with VP Of AI Factory, influencing platform investment, architecture direction, and build‑vs‑buy decisions across the enterprise.
• Partner with the CTO, Chief Data Officer, VP Of AI Factory and clinical leadership to ensure AI engineering capabilities support the full AI lifecycle from research and experimentation to scalable production deployment.

AI Platform & MLOps Infrastructure

• Architect and operate a cloud‑native, enterprise‑grade AI platform that supports model training, evaluation, versioning, deployment, and monitoring at scale.
• Establish and enforce MLOps best practices including CI/CD pipelines for model development, automated testing, model registry management, and drift detection.
• Drive infrastructure strategy across compute, orchestration (e.g., Kubernetes, Airflow), and data pipelines to optimize cost, performance, and regulatory compliance.

Model Development & Production Deployment

• Lead engineering teams responsible for developing, fine‑tuning, and deploying machine learning models and LLM‑powered solutions into production healthcare environments.
• Oversee integration of AI models with core health plan systems including claims platforms, EHRs, care management tools, and member‑facing applications ensuring high availability, low latency, and auditability.
• Champion rigorous model evaluation, A/B testing, and continuous improvement frameworks appropriate for high‑stakes healthcare use cases.

Team Building & Engineering Culture

• Recruit, develop, and retain a world‑class team of AI engineers, ML engineers, and data scientists with deep healthcare domain exposure.
• Build an engineering culture rooted in technical ownership, clinical accountability, psychological safety, and continuous learning.
• Define career frameworks, leveling guides, and growth paths for the AI engineering organization.

AI Governance, Compliance & Risk Management

• Establish and enforce AI engineering standards covering responsible AI, bias detection, model explainability, and clinical safety in alignment with HIPAA, CMS regulations, and applicable state requirements.
• Ensure all AI systems and infrastructure meet the company's security, data privacy, and compliance standards, protecting sensitive member and clinical data.
• Partner with Office of CEO, Legal, Compliance, Security, and Risk teams to identify, assess, and mitigate technical and ethical risks associated with AI deployments, including third‑party and vendor AI solutions.
• Develop and maintain AI governance policies and audit frameworks to support regulatory reporting and internal oversight.

Stakeholder Engagement & Cross‑Functional Collaboration

• Collaborate with Office of CEO, clinical,…