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Hippocratic AI is seeking a Forward Deployed Engineer to own the technical delivery of AI deployments that transform healthcare operations. You will embed with health system customers to architect, build, launch, and operate production conversational AI agents that handle real clinical workflows and impact thousands of patient interactions.
In your first 90 days, you will complete end-to-end ownership of your first AI deployment: design and implement RAG pipelines grounded in customer clinical data, build tool-calling and Model Context Protocol (MCP) integrations connecting agents to customer systems (EHRs like Epic/Cerner/Athena, data warehouses, operational tools), execute production go-live, and establish monitoring systems. By 12 months, you will have deployed multiple agents across assigned health systems, built reusable AI patterns and frameworks, become the trusted technical partner for customers' hardest AI problems, and generated measurable evidence of operational and clinical impact.
You will design and implement RAG pipelines that ground conversational AI in customer clinical data while managing retrieval latency and data governance. Build tool-calling and MCP architectures enabling secure agent interactions with customer systems, handling errors gracefully and enforcing safety constraints. Develop production Python code using LangChain, LangSmith, and modern AI frameworks to implement advanced LLM techniques (RAG, prompt engineering, LLM-as-judge, chain-of-thought reasoning). Execute end-to-end deployments including infrastructure setup, integration testing, production monitoring, cutover planning, and go-live execution. Monitor and own production systems by instrumenting deployed agents, responding to incidents, troubleshooting with customers, and implementing reliable fixes. Partner with customers as technical expert, explaining AI system architecture, capabilities, and limitations.
You will work alongside Deployment Strategists, engineers, and clinical experts, embedded with customers but tightly connected to the core AI team. This role offers high technical ownership and autonomy in the field with direct access to product, ML research, and engineering leadership. The culture emphasizes shipping real systems, owning outcomes, and solving problems proactively.
This is a remote role with significant field presence requiring approximately 25% travel to customer sites across the United States and quarterly travel to Menlo Park headquarters for strategic planning and technical collaboration.
