Responsibilities:

• End-to-End Product Ownership: Define and own the product vision, strategy, and roadmap for Clinical AI tools with no PM layer above you.
• RAG Pipeline Design & Iteration: Architect, implement, and continuously improve the RAG infrastructure powering clinical decision support: chunking strategies, embedding models, vector database design, retrieval and reranking approaches, and evaluation frameworks.
• Prompt Engineering & Model Behavior: Design and iterate on prompt strategies, system instructions, and guardrails to produce reliable, clinically appropriate outputs.
• AWS Infrastructure: Deploy and maintain scalable, HIPAA-compliant AI infrastructure on AWS.
• Clinical Data & Integration: Work with healthcare data sources (EHR-adjacent, structured and unstructured clinical content) and integrate AI outputs into clinical workflows in ways that are accurate, auditable, and safe.
• Clinical Stakeholder Partnership: Own the relationship with clinicians and clinical operations directly , there is no PM intermediary.
• Technical Collaboration: Partner with backend and frontend engineers to integrate AI capabilities into the broader product.
• Staying Current: Actively track developments in applied AI research, RAG techniques, and agentic workflow design.
• Stakeholder Communication & Alignment: Translate technical AI concepts and tradeoffs for clinical and operational stakeholders.

Requirements:

• 5–8 years of experience in software or AI/ML engineering, with a meaningful portion in applied AI product development.
• Hands-on experience building and operating RAG systems in production.
• Strong Python skills; comfortable building pipelines, writing evaluation harnesses, and iterating on model behavior programmatically.
• SQL proficiency sufficient to query data independently, pull your own product metrics, and answer analytical questions without waiting on a data team.
• Experience deploying AI workloads on AWS; familiarity with relevant services (e.g., Bedrock, SageMaker, Lambda, RDS/Aurora, S3) and the tradeoffs between them.
• A product mindset , you think about user problems and outcomes, not just technical implementation, and you can write a clear spec as readily as a pull request.
• Experience with API design and integration, and the ability to collaborate closely with frontend and backend engineers without being a bottleneck.
• Healthcare or regulated-domain experience preferred; you understand why accuracy, auditability, and safe failure modes matter more in clinical contexts than in most.
• Familiarity with LLM safety tooling (e.g., guardrails, output validation frameworks) and an instinct for where AI systems can fail quietly.

Additional Information:

• Pay & Perks: Fully remote opportunity, medical, dental, and vision insurance, 401K retirement plan with company match, up to 20 days of PTO per year + company holidays, up to 14 weeks of parental leave (12 for non-birthing parents), annual work from home stipend for remote employees.

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