Technical Product Manager - AI Platform, Remote

Primary Duties:

• Partner with business owners to cultivate a shared vision for the problem space, constraints, priorities, and ideal end state, and be able to articulate and advocate for this perspective.
• Lead the full lifecycle of ML and LLM platform workstreams—from data ingestion, training, and deployment to ongoing optimization of live user workflows based on performance metrics and feedback.
• Work with internal teams and end users to develop a deep understanding of requirements, perform thoughtful solution design, use data to test hypotheses, and support teams throughout execution.
• Write detailed user stories for new features, capturing descriptions of business rationale, requirements, and success criteria defined by measurable outcomes.
• Develop short- and long-term roadmaps that deliver maximum value with minimum risk and assume ongoing iteration.
• Partner with AI Researchers to mature proofs-of-concept into production-ready capabilities; perform exploration of user feedback, healthcare records, and validation data to validate model performance.

Minimum Qualifications:

• 6+ years of product management experience in technology, technology-enabled services, or SaaS.
• Strong understanding of artificial intelligence and/or machine learning technologies.
• Experience using data and primary research to inform solution design and build business understanding.
• Familiarity with Agile teams, Jira, and the software development lifecycle.
• Knowledge of APIs, DevOps, enterprise software development, and cloud infrastructure (e.g., Databricks, AWS, GCP, Azure).
• Understanding of data engineering principles.
• Ability to communicate technical trade-offs to non-technical stakeholders.
• Skilled at translating ambiguous product requirements into a technical roadmap.

Preferred Knowledge, Skills and/or Abilities:

• Experience leading AI/ML platform products and scaling platforms vertically and horizontally.
• Track record of building and launching AI/ML platforms, tools, or internal services.
• Deep knowledge of AI/ML product lifecycle, MLOps, and scalable AI infrastructure (training, deployment, monitoring, observability, reliability).
• Experience with large language models (LLMs) and generative AI technologies, including prompt engineering strategies and VLMs.
• Background as a data scientist or backend engineer.
• Fluency in translating technical concepts into value propositions and storytelling for diverse stakeholders.
• Clinical Data Literacy: Familiarity with EHR data, Claims, or population health datasets.
• Experience in healthcare technology environments, particularly physician-facing products or work with clinical datasets (EHR, Claims, Population Health datasets).

Physical Requirements:

• Sitting for prolonged periods of time. Extensive use of computers and keyboards. Occasional walking and lifting may be required.