Senior Technical Product Manager (AI Data Platform), Remote

Role Overview

Senior Technical Product Manager on the AI Data Platform team at Aledade. You will define and drive the roadmap for an AI Data Platform that supports internal stakeholders and external AI products, enabling LLM-powered tools to retrieve and use relevant healthcare data for value-based care workflows.

Responsibilities

• Partner with business owners to align on vision, problem constraints, priorities, and target end state; articulate and advocate for the product perspective.
• Lead the full lifecycle of ML/LLM platform workstreams:
  • data ingestion
  • training
  • deployment
  • ongoing optimization using performance metrics and user feedback.
• Gather requirements with internal teams and end users; perform solution design and use data to test hypotheses.
• Write detailed user stories including business rationale, requirements, and measurable success criteria.
• Develop short- and long-term roadmaps that maximize value while minimizing risk through iterative delivery.
• Work with AI researchers to mature proofs-of-concept into production-ready capabilities.
• Conduct hands-on exploration of user feedback, healthcare records, and validation data to assess model performance.

Requirements (Minimum Qualifications)

• 8+ years of product management experience in technology, technology-enabled services, or SaaS.
• Strong understanding of AI and/or ML and related technologies.
• Experience using data and primary research to inform solution design and build internal business understanding.
• Experience with Agile teams, Jira, and the software development lifecycle.
• Strong understanding of APIs, DevOps, enterprise software development, and cloud infrastructure (databricks/AWS/GCP/Azure) plus data engineering principles.
• Ability to communicate technical trade-offs to non-technical stakeholders.
• Comfort translating ambiguous requirements into a technical roadmap.

Preferred Qualifications

• Experience leading products for an AI/ML platform team and scaling platform capabilities vertically and horizontally.
• Track record building and launching AI/ML platforms, tools, or internal services enabling other product teams.
• Deep understanding of the AI/ML product lifecycle, MLOps, and scalable AI infrastructure (training, deployment, monitoring, observability, reliability).
• Experience with LLMs/generative AI, including prompt engineering strategies and VLMs.
• Experience as a data scientist or backend engineer.
• Clinical data literacy (EHR data, claims, population health datasets) and experience in healthcare technology environments.