Principal AI & Automation Engineer

Role overview

Strategy and automation delivery

• Maintain a multi-year roadmap supporting Stars, risk adjustment, payment accuracy, prior authorization, clinical quality, and member experience.
• Prioritize high-ROI use cases with C-suite and senior leaders.
• Lead enterprise RPA, workflow orchestration, and process-intelligence solutions across Claims, UM, Provider Operations, and Member Services.
• Set standards and governance for automation development, documentation, and change management.

Engineering and collaboration

• Own selection and adoption of AI/ML platforms, cloud services, and automation tools integrated with data platforms and security controls.
• Set engineering standards for CI/CD, MLOps, testing, observability, and documentation.
• Partner across Product, Data Engineering, Clinical Operations, Finance, Compliance, and Security to deliver solutions and track outcomes.
• Report strategy, progress, and ROI to executives and governance bodies.

Responsible AI and business ownership

• Work with Legal, Compliance, and Privacy on CMS, HIPAA, and internal governance compliance.
• Implement bias detection, explainability, auditability, and change control for AI systems affecting care and financial outcomes.
• Own the operating budget, evaluate and manage vendors, and oversee cloud and platform spending.

Required experience

• 8–12 years of progressive software engineering, data science, or AI/ML experience, including 3–5 years at senior level.
• Track record delivering production-grade AI/ML and large-scale automation in regulated or enterprise settings.
• Deep expertise in machine learning, NLP, generative AI (LLMs and RAG), agentic frameworks, RPA, and orchestration.
• Experience managing budgets, vendors, and technology platform decisions at department or function level.

Education and training

• Bachelor’s degree in Computer Science, Computer or Electrical Engineering, Mathematics, Data Science, or a related quantitative field; equivalent education and demonstrated experience may be considered.
• Senior-level AI/ML engineering, cloud-platform, and enterprise-automation proficiency; formal training or self-directed mastery is accepted.
• Leadership-level working knowledge of cloud AI/ML governance and platform management on AWS, Azure, or GCP; certification or equivalent experience is accepted.

Preferred qualifications

• Healthcare, Medicare Advantage, managed care, or payer experience is preferred, as is knowledge of HL7 FHIR, ICD-10/CPT, or DICOM.
• Building an AI or automation engineering function, published research, conference presentations, or AI/ML thought leadership is preferred.
• A relevant master’s degree or PhD, advanced cloud or RPA certifications, and AI strategy, responsible AI, MLOps, or cloud AI training are preferred.

Pay range

• Pay range is $172,364–$258,547 yearly; the range may vary with market location, education, responsibilities, and experience.

Physical functions