Forward Deployed Engineer (FDE)
The Forward Deployed Engineer is the technical owner for AI deployments. You will be a core contributor to our agentic AI platform. This is a high-ownership role where you work closely with Deployment Strategists and customers, building real production systems that directly impact healthcare operations. You need to be a strong software engineer who enjoys working in customer environments and taking ownership of end-to-end system reliability.
You have expertise in software development in python, experience with frameworks such as langchain and langsmith, deep understanding of LLM techniques such as RAG, LLM as a judge, and MCP/tool calling.
What Success Looks Like
AI Innovation: You use your expertise in AI Engineering to solve cutting-edge problems in healthcare-focused conversational AI, applying RAG, tool-calling, and advanced LLM techniques to novel customer challenges
Customer Problem-Solving: You identify issues early through close monitoring and proactive communication, often solving problems before they affect clinical operations
Reliable AI Systems: You build integrations that connect reliably to customer systems (EHRs, data warehouses, operational tools), handling errors gracefully and monitoring for anomalies
Smooth Deployments: You execute deployment plans without surprises—infrastructure is ready, integrations are tested, cutover is planned and executed professionally
Production Ownership: You monitor deployed systems, respond quickly to incidents, and drive operational improvements that keep agents running smoothly
Technical Partnership: You help customers understand the AI system architecture, debug issues collaboratively, and build their confidence in the solution
Core Responsibilities
AI Innovation & Problem-Solving – Identify customer challenges and design AI solutions using advanced LLM techniques (RAG, tool calling, LLM-as-judge); implement novel approaches to healthcare AI problems
RAG Pipeline Implementation – Design and implement retrieval-augmented generation pipelines that ground LLM responses in customer data, ensuring accuracy and clinical relevance
Tool & MCP Architecture – Implement tool-calling architectures and Model Context Protocol (MCP) connections that enable agents to interact with customer systems safely
Python AI Development – Build production Python code using LangChain, LangSmith, and modern AI frameworks to create reliable AI systems
Infrastructure & Deployment – Set up secure, monitored production environments; manage deployment and go-live activities
Production Monitoring & Support – Monitor deployed systems, respond to incidents, troubleshoot problems with customers, implement fixes
What You Bring
Must Haves
3-5 years of software engineering experience with strong Python fundamentals and production software development experience
Hands-on experience with LLM frameworks (LangChain, LangSmith) and understanding of modern LLM development patterns
Deep understanding of LLM techniques: RAG, prompt engineering, tool calling, LLM-as-judge, and related patterns
Experience building integrations with APIs, databases, or enterprise systems; comfort with async patterns and error handling
Bachelor's degree in Computer Science (or related field) from a top ranked university.
Nice to Haves
Experience with Model Context Protocol (MCP) or similar approaches for tool integration
Healthcare IT experience (EHR integrations, FHIR, HL7, healthcare data standards)
Production DevOps or infrastructure experience; ability to set up monitoring and incident response
Experience deploying AI systems or working with LLMs in production environments
Why Hippocratic AI
You're innovating in AI-native healthcare. You're not building traditional integrations—you're solving cutting-edge problems in conversational AI for healthcare. Every RAG pipeline you design, every tool-calling pattern you implement, every LLM optimization you discover contributes to healthcare transformation.
You work with world-class AI engineers and clinical experts from Google, Meta, Microsoft, NVIDIA, Johns Hopkins, Washington University, Stanford. You'll tackle harder AI problems alongside smarter people. You'll grow your AI expertise faster here than almost anywhere.
Backed by $404M from top-tier AI and healthcare investors—CapitalG, a16z, General Catalyst, Kleiner Perkins, plus strategic health system investors. This validates the category and gives you the resources to focus on innovation without runway concerns.
This is category creation. You're defining how LLM agents interact with healthcare systems, how RAG grounds clinical AI, how to deploy AI safely at scale. You're not following playbooks—you're writing them..
Ready to Apply?
If you've built production AI systems, thrive at the edge of technical and human complexity, and want your work to matter in the most direct sense possible — we'd like to meet you.
Please be aware of recruitment scams impersonating Hippocratic AI. All recruiting communication will come from @hippocraticai.com email addresses. We will never request payment or sensitive personal information during the hiring process.
Requires 3–5 years of software engineering experience, strong Python, LangChain and LangSmith experience, LLM techniques expertise, enterprise integrations, and a bachelor's degree in computer science or related field.
Key Responsibilities
- designing AI solutions
- implementing pipelines
- monitoring systems
Skills & Tools
Python, LangChain, LangSmith, RAG, LLM, Model Context Protocol (MCP), EHR, FHIR, HL7
Job Details
- Category: Software Development
- Seniority: Mid Level
- Commitment: Full Time
- Workplace: Remote — United States
- Languages: English
About Hippocratic AI
An artificial intelligence company developing conversational AI systems for healthcare. — Industry: Information Technology