Manager of Applied AI Products

Accountabilities:

• • Partner with product leadership to shape the AI roadmap, contributing technical and healthcare domain expertise to prioritization, product strategy, and investment decisions.
  • Translate provider pain points, clinical workflow gaps, and healthcare data challenges into clearly defined AI product opportunities and actionable requirements.
  • Establish evaluation frameworks to measure AI feature performance, clinical utility, reliability, adoption, and business impact.
  • Engage directly with health center leaders, clinicians, administrators, prospects, and strategic clients to conduct discovery, validate product direction, gather feedback, and communicate AI capabilities.
  • Personally design, develop, and ship production AI features, including LLM integrations, retrieval-augmented generation (RAG) pipelines, vector search, and healthcare data workflows.
  • Own AI architecture end-to-end, covering data ingestion, retrieval strategies, data flows, APIs, system design, deployment, scalability, reliability, and implementation quality.
  • Ensure AI solutions are designed and operated with appropriate HIPAA, PHI, privacy, security, and compliance considerations.
  • Work directly alongside engineers and product colleagues, contributing through code reviews, technical design, pairing, and hands-on implementation rather than functioning solely as a coordinator.
  • Raise the technical bar for AI development by establishing practical engineering, evaluation, security, and responsible-AI practices.
  • Serve as an internal AI advisor, helping non-engineering teams identify valuable use cases and build AI-assisted workflows responsibly.
  • Review AI-powered tools and automations created by employees before production use, assessing reliability, security, PHI exposure, and compliance risks.
  • Establish and maintain a lightweight governance and review process for internally developed AI tools and recommend company-wide acceptable-use practices.
  • Build AI literacy through documentation, working sessions, coaching, and direct support across the organization.
  • Represent the organization’s AI strategy in client discussions, prospect conversations, RFPs, and relevant industry forums when appropriate.

  Requirements:

  • Must currently reside in the United States and be authorized to work in the U.S. without current or future visa sponsorship.
  • Substantial experience within healthcare IT is required; candidates without meaningful healthcare technology experience will not be considered.
  • Experience in healthcare SaaS, health systems, digital health, or EHR environments, with practical understanding of clinical workflows and how providers document, order, communicate, and manage information.
  • Working knowledge of healthcare interoperability and data standards, including HL7 v2, FHIR (R4 preferred), CCD/CCDA, and common healthcare integration patterns.
  • Direct experience working with HIPAA compliance, protected health information (PHI), de-identification, privacy requirements, and the regulatory constraints that influence healthcare system design.
  • Exposure to college health, student health, behavioral health, or related clinical environments is strongly preferred.
  • 6+ years of experience in product engineering, technical product management, or a comparable hands-on hybrid role within B2B SaaS, including at least 3 years personally building AI or ML-powered features in production.
  • Demonstrated portfolio of AI systems personally designed and built, with the ability to discuss architecture, implementation decisions, and code-level contributions in detail.
  • Proven ability to contribute across the complete product lifecycle, from strategy and discovery through technical delivery, launch, and customer adoption.
  • Hands-on production experience integrating LLM APIs such as OpenAI, Anthropic, or comparable technologies within healthcare or enterprise environments.
  • Strong understanding of RAG architectures, including retrieval pipeline design, chunking, grounding, evaluation, vector databases, embedding models, and unstructured data indexing.
  • Comfortable working with data modeling, SQL, analytics workflows, APIs, and backend services involving large structured or unstructured healthcare datasets.
  • Ability to operate effectively at both strategic and technical levels, from roadmap discussions with senior executives to architecture reviews and hands-on development with engineers.
  • Strong client-facing, written, verbal, presentation, and facilitation skills, with the ability to explain sophisticated AI and clinical concepts to technical, clinical, operational, and executive audiences.
  • Demonstrated ability to balance product vision, technical execution, customer needs, compliance, and business outcomes.
  • A player/coach mindset is essential: this position requires regular hands-on technical contribution and is not suited to candidates seeking a purely managerial role.

  Benefits:

  • Base salary: $120,000–$145,000 USD, excluding annual bonus where applicable.
  • Compensation may vary based on market conditions, location, job-related skills, experience, and other relevant factors.
  • Fully remote position within the United States.
  • Direct access to senior leadership and meaningful influence over product and AI strategy.
  • Opportunity to work on AI capabilities with tangible impact across healthcare and clinical workflows.
  • High-ownership environment with low bureaucracy and an emphasis on accountability and technical craft.
  • Opportunity to personally build and ship AI products rather than focusing exclusively on strategy or management.
  • Exposure to a healthcare platform serving hundreds of health and counseling centers.
  • Collaborative environment focused on responsible AI innovation, product quality, and measurable customer outcomes.
  • Opportunity to help establish AI governance, best practices, and literacy across a growing organization.
  • Inclusive workplace committed to equal employment opportunity and a diverse, supportive culture.