Technical AI Program Manager

MiniMed•Los Angeles, CA

18h•Hybrid

About The Position

The Technical AI Program Manager is a senior individual contributor responsible for driving the end-to-end ownership of AI/ML products across MiniMed's enterprise business functions including Commercial, Marketing, Finance, and Quality. This role serves as the strategic and technical bridge between AI Engineering, Data Science, and cross-functional business partners within MiniMed's Transformation Organization. The Technical AI Program Manager leads use case discovery, defines product vision and roadmap, and ensures the delivery of AI solutions that generate measurable business value in a regulated MedTech environment. This position is hybrid onsite in Atlanta, GA or Northridge, CA

Requirements

Bachelor’s degree in Computer Science, Data Science, Engineering, Information Systems, or a related technical field and 5+ years of experience
Or, advanced degree and 3+ years of experience

Nice To Haves

Proven track record of delivering AI/ML products to production in an enterprise environment
Demonstrated experience serving multiple business functions simultaneously such as Commercial, Finance, Marketing, or Quality
Strong working knowledge of the ML model lifecycle including training, evaluation, deployment, and monitoring
Familiarity with LLM patterns including RAG, fine-tuning, prompt engineering, and embeddings
Understanding of MLOps frameworks and CI/CD pipelines for machine learning
Exposure to data platform concepts including data lakehouses, vector databases, APIs, and ETL/ELT pipelines
Cloud AI services familiarity with Azure AI, AWS SageMaker, or Google Vertex AI
Proficiency in Agile tooling including Jira, Confluence, and Jira Align or equivalent platforms
Experience in a regulated industry such as medical devices, pharmaceuticals, or financial services
Experience with enterprise AI governance frameworks and Responsible AI programs
Background in large-scale digital transformation programs inclusive of organizational change management
Knowledge of generative AI enterprise platforms such as OpenAI, Azure OpenAI, or Anthropic Claude
Exposure to commercial CRM or ERP platforms such as Salesforce or SAP and their AI extension ecosystems
Certified Scrum Product Owner (CSPO)
SAFe Product Owner / Product Manager (POPM)
SAFe Agilist (SA) or equivalent
AWS, Azure, or GCP AI or Data certifications

Responsibilities

Define and own the AI/ML product vision, roadmap, and portfolio strategy across Commercial, Marketing, Finance, and Quality business functions
Partner with business leaders to identify, prioritize, and validate AI use cases with clear ROI and measurable success criteria
Translate complex business problems into well-defined AI product opportunities and communicate a compelling product narrative to senior stakeholders
Own the full AI/ML product lifecycle from use case discovery and data readiness through model deployment, monitoring, and continuous improvement
Define AI-specific acceptance criteria including model performance thresholds, explainability requirements, and human-in-the-loop workflows
Maintain technical fluency in LLM architecture patterns (RAG, fine-tuning, prompt engineering), MLOps pipelines, data platform concepts, and cloud AI services to effectively partner with engineering and data science teams
Serve as Product Owner within Scrum teams, owning the product backlog and leading all sprint ceremonies including planning, standups, reviews, and retrospectives
Prioritize backlog using value-based frameworks (WSJF, RICE, MoSCoW) and operate within a SAFe environment including PI Planning and ART-level ceremonies
Drive sprint velocity and delivery predictability while mentoring junior product owners on AI product ownership best practices
Lead use case discovery workshops and build trusted partnerships with business domain leaders across multiple functions to surface and prioritize high-value AI opportunities
Develop comprehensive AI business cases including cost-benefit analysis, automation projections, and risk-adjusted value estimates
Facilitate alignment between business stakeholders and technical teams while driving organizational readiness and change management for AI product adoption
Define and track AI-specific KPIs including model accuracy, adoption rates, automation rates, and business outcome metrics, reporting portfolio ROI to senior leadership
Design and execute A/B testing and experimentation frameworks to evaluate AI feature performance and feed insights back into the product roadmap