Forward-Deployed Health AI Engineer

Hippocratic AI Inc.

United States

On-site

USD 150,000 - 230,000

Full time

4 days ago
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Job summary

Hippocratic AI Inc. seeks a Forward Deployed Engineer to own AI deployments that transform health systems by embedding with customers to build, launch, and operate production conversational AI agents.

You will design RAG pipelines grounded in clinical data and connect agents to EHRs and data warehouses while ensuring safety and reliability. You will lead end-to-end deployments, monitor production systems, and partner with product, ML research, and engineering leadership to ship scalable AI in

Qualifications

  • LLM techniques: RAG, prompt engineering, tool calling, LLM-as-judge.
  • 3+ years of professional software engineering experience.
  • Experience building integrations with APIs, databases, or enterprise systems.

Responsibilities

  • Own end-to-end AI deployments with health systems.
  • Embed with customers to build, launch, and operate production AI agents.
  • Design and implement RAG pipelines grounded in customer data.
  • Build tool-calling and MCP architectures for secure interactions with customer systems.
  • Develop production Python code using LangChain and LangSmith.
  • Execute deployments with infrastructure setup, testing, monitoring, and go-live.

Skills

LLM techniques
LangChain/LangSmith
Python
Async patterns & reliability
APIs & enterprise integrations
FHIR/HL7 healthcare data knowledge

Education

Bachelor's degree in Computer Science or related field

Tools

LangChain
LangSmith
Model Context Protocol (MCP)
EHR integrations (Epic, Cerner, Athena)

Job description

Hippocratic AI Inc. seeks a Forward Deployed Engineer to own AI deployments that transform health systems by embedding with customers to build, launch, and operate production conversational AI agents.

You will design RAG pipelines grounded in clinical data and connect agents to EHRs and data warehouses while ensuring safety and reliability. You will lead end-to-end deployments, monitor production systems, and partner with product, ML research, and engineering leadership to ship scalable AI in

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