Technical AI Product Lead (CMH Health)

Individual(s) must be legally authorized to work in the United States without the need for immigration support or sponsorship from Milliman now or in the future. Milliman’s CMH Health practice is seeking a Technical AI Product Lead who will function as “The Designer,” by creating solutions and making appropriate tradeoffs while prioritizing cost reduction and system reliability with a focus on efficiency. As a feature owner, the Technical AI Product Lead will own specific features from concept to client delivery within speed, cost, and quality constraints and interact with internal consultants to understand user needs and perform initial reasonableness checks.

Who We Are The beginning of a new Data & AI decade that will reshape work and society has begun. Milliman is stepping boldly into this future with a clear goal of reinventing how we and our clients conduct business with data & AI.

With over 5,000 professionals serving our clients to protect the health and financial well-being of people everywhere, Milliman’s focus on AI brings together our technologists, consultants, and professionals in every corner of the healthcare ecosystem. Independent for over 75 years, we are helping companies take on some of the world’s most critical and complex issues, including retirement funding and healthcare financing, risk management and regulatory compliance, data analytics and business transformation.

Job Responsibilities

• Meet task and project deadlines through active dependency management and delivery cadence
• Create quality outputs with pragmatic tradeoffs and repeatable delivery
• Follow QRM with reviewable design decisions and risk tradeoffs
• Understand core tech stacks and make pragmatic architecture and automation decisions
• Delegate and teach effectively, with meaningful execution delegated to others when appropriate
• Identify client problems and design features with clear tradeoffs
• Manage feature dependencies and budgets
• Prepare client communications that explain tradeoffs and results clearly
• Act as a trusted partner for features and tradeoffs
• Meet or exceed client expectations through repeatable delivery and improved efficiency
• Coach staff in tool usage, patterns, and feedback
• Handle conflict productively and build trust
• Provide and obtain timely feedback with clear expectations
• Optionally participate on market segment committees
• Identify scalable opportunities and support pilots
• Support practice marketing efforts as appropriate
• Assist with broader practice needs such as mentoring and interviewing

Minimum Requirements

• Bachelor’s degree in Computer Science, Engineering, or a related field.
• 4+ years of experience in software development with a focus on AI and machine learning applications.
• Experience working with foundational model APIs (OpenAI, Anthropic, Gemini, Llama)
• Proficiency in programming languages such as Python and C#, and experience with AI frameworks like LangChain, OpenAI, LlamaIndex, PromptFlow, PyTorch, or similar.
• Experience implementing and integrating pre-trained AI models into applications.
• Strong understanding of machine learning algorithms and natural language processing techniques.
• Familiarity with software development practices, version control systems, and agile methodologies.
• Experience working with cloud technologies (Azure) and handling large datasets (e.g., Azure Synapse, Databricks, Data Lakes).
• Excellent problem-solving skills and the ability to troubleshoot complex AI-related issues.
• Strong communication skills with the ability to work collaboratively in a team environment.
• Knowledge of the healthcare industry and regulatory considerations is preferred.

Competencies and Behaviors that Support Success in this Role

• Execution and Ownership: Ownership mindset, reliable commitments, prioritization, and delivery planning
• Technical and AI Leverage: Technical depth, systems thinking, architecture judgment, and practical automation
• Quality, Risk, and Defensibility: Validation discipline, risk awareness, and controls mindset
• Domain, Product, and Outcomes: Domain curiosity, product thinking, and adoption orientation
• Communication and Influence: Written communication, oral communication, and stakeholder management
• Leadership and Team Scaling: Coachability, delegation, coaching, and team contribution
• Mindset: Impact-first, systems-thinking, pragmatic MVP judgment
• Discovery: Internal consul…