Aledade
- Define and deliver the roadmap to drive execution and scale of the AI Platform that supports internal stakeholders and external AI products.
- Operate at the intersection of machine learning systems, data engineering, and applied healthcare AI.
- Partner closely with AI engineers, data scientists, and clinical leadership to deliver production-grade systems that support reliable inference pipelines across millions of patient records.
- Contribute to the improvement of quality and cost of care for over 2 million patients served by Aledade providers.
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:
- 8+ 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.
Who We Are:
What Does This Mean for You?
Originally posted on Himalayas
To apply for this job please visit himalayas.app.
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