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Primary Duties
- Work with product, engineering, and teams 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 the 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 detailed descriptions of business rationale, requirements, and success criteria that are 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 hands-on exploration of user feedback, healthcare records and validation data to validate model performance.
Minimum Qualifications
- 12+ years of experience in product management in technology, technology-enabled services industry, or a SaaS product.
- Robust understanding of AI and/or machine learning, and related technologies.
- Experience using data and primary research to inform solution design and build internal business understanding.
- Experience with Agile teams, Jira, and understanding the software development lifecycle.
- Strong understanding of APIs, DevOps, enterprise software development, cloud infrastructure (databricks/AWS/GCP/Azure), and data engineering principles.
- Exceptional ability to communicate technical tradeoffs to non-technical stakeholders.
- Comfortable with translating ambiguous product requirements into technical roadmap.
Preferred Knowledge, Skills and/or Abilities
- Experience working on or leading products for an AI/ML Platform team and building a platform to scale vertically and horizontally.
- Proven track record of building and launching AI/ML platforms, tools, or internal services that enable other product teams.
- Deep understanding of the AI/ML product lifecycle, MLOps, and scalable AI infrastructure (e.g. model training, deployment, monitoring, observability, reliability.)
- Experience with LLMs and generative AI technologies, including prompt engineering strategies and VLMs.
- Experience working as a data scientist or backend engineers.
- Strong ability to translate technical concepts and platform capabilities into value propositions and storytelling skills to communicate diverse internal stakeholders.
- Experience in a healthcare technology environment, including physician-facing products or working with clinical datasets (EHR data, Claims, Population Health datasets, etc.)
Physical Requirements
Sitting for prolonged periods of time. Extensive use of computers and keyboard. Occasional walking and lifting may be required.
