Hippocratic AI
Deployment Strategist (York, PA)
York, PA · Hybrid · Full-time · Posted Oct 2, 2026
- Experience
- 4+ years; experience may have been accrued in any of the listed relevant fields.
- Education
- BA/BS in a technical field (engineering, science, analytics, economics, or similar).
About the job
Own end-to-end healthcare AI deployments, from workflow discovery and solution design through configuration, launch, adoption, and performance measurement.
What you'll do
- Design and build agents for complex healthcare conversations; map data flows and partner with engineering on implementation.
- Lead customer deployments, including stakeholder engagement, workflow configuration, timelines, documentation, and blocker resolution.
- Track deployment performance, capture reusable implementation practices, and inform product and process improvements.
What they ask for
- 4+ years of relevant experience in deployment, implementation, strategic operations, consulting, solution architecture, or technical program management.
- Direct experience serving healthcare customers or working inside a healthcare organization, with working knowledge of provider-side, payor-side, or life sciences workflows.
- Ability to reason about unfamiliar data models and hands-on comfort with JSON files, terminals, command-line coding assistants, and git workflows.
- Track record managing complex customer engagements across stakeholders; BA/BS in a technical field (engineering, science, analytics, economics, or similar).
Nice to have
- SQL; Epic experience or certification; clinical background; forward-deployed, implementation, or solutions work at an AI, data platform, or health-tech company.
- HL7 or FHIR fluency; experience in utilization management, prior authorization, care management, revenue cycle, or value-based care; exposure to production LLM-based or agentic products.
Tools
JSON, terminals, command-line coding assistants, git, SQL, Epic, Clarity, Caboodle
AI focus
Design, build, configure, and deploy AI agents for complex healthcare conversations; use deployment insights to support AI feature development and improvements.
Model-written summary · the original posting is authoritative