Forward Deployed Engineer

Role Mission

As HAI's Forward Deployed Engineer, you will be the technical owner of AI deployments that directly transform how health systems operate. You'll embed with customers to build, launch, and operate production conversational AI agents—architecting systems that handle real clinical workflows and impact thousands of patient interactions. This role exists because healthcare organizations are ready to deploy breakthrough AI at scale, and they need a world-class AI engineer who can build reliable, innovative systems in the field.

What You Will Accomplish

Own your first major outcome: By day 90, you will have completed end-to-end ownership of your first AI deployment: designed and implemented a RAG pipeline grounded in customer data, built tool-calling and MCP integrations connecting our agents to customer systems ( EHRs, data warehouses, operational tools ), executed a production go-live with zero surprises, and established monitoring that catches anomalies before customers do.

Drive lasting impact: At 12 months, you will have deployed multiple agents across your assigned health system, built reusable AI patterns and frameworks that accelerate future deployments, become the trusted technical partner that customers rely on to solve their hardest AI problems, and generate measurable evidence that our agents improve operational reliability and clinical outcomes—validating our technology in production healthcare environments.

The Team

You'll work alongside Deployment Strategists, engineers, and clinical experts—embedded with customers but tightly connected to our core AI team. You'll operate with high technical ownership and autonomy in the field, with direct access to our product, ML research, and engineering leadership. This is a culture of shipping real systems, owning outcomes, and solving problems before they become crises.

What You Will Do

• Design and implement RAG pipelines that ground conversational AI responses in customer clinical data, ensuring accuracy, safety, and relevance to healthcare workflows while managing retrieval latency and data governance

• Build tool-calling and Model Context Protocol (MCP) architectures that enable AI agents to interact securely with customer systems— EHRs (Epic, Cerner, Athena), data warehouses, and operational tools —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 ) solving novel healthcare AI problems

• Execute end-to-end deployments including infrastructure setup, integration testing, production monitoring configuration, cutover planning, and go-live execution—ensuring deployments happen on schedule without surprises

• Monitor and own production systems by instrumenting deployed agents, responding quickly to incidents, troubleshooting issues collaboratively with customers, and implementing fixes that keep systems running reliably

• Partner with customers as technical expert , explaining AI system architecture, helping teams understand capabilities and limitations, and building confidence in the solution through proactive communication and problem-solving

Location Requirement

This is a remote role with significant field presence. You must be willing to travel approximately 25% of the time to customer sites across the United States to deploy and support AI systems in healthcare environments. Additionally, you are expected to travel to our Menlo Park headquarters quarterly for strategic planning, team alignment, and technical collaboration.

Basic Qualifications

• Bachelor's degree in Computer Science, Software Engineering, or a related technical field

• 3+ years of professional software engineering experience with strong Python fundamentals and production software development experience

• Hands-on experience with LLM frameworks ( LangChain, LangSmith , or similar) and deep understanding of modern LLM development patterns and best practices

• Deep expertise in LLM techniques including retrieval-augmented generation (RAG), prompt engineering, tool calling, LLM-as-judge , and related advanced patterns

• Demonstrated experience building integrations with APIs, databases, or enterprise systems; comfort with async patterns, error handling, and reliability engineering

Preferred Qualifications

• Experience with Model Context Protocol (MCP) or similar frameworks for tool integration and multi-system orchestration

• Healthcare IT experience, including EHR integrations (Epic, Cerner, Athena), FHIR, HL7 , or healthcare data standards

• Production DevOps or infrastructure experience, including setting up monitoring, alerting, logging, and incident response systems

• Track record deploying AI systems or working with LLMs in production environments, managing latency, reliability, and operational complexity

• Experience in mission-critical or safety-sensitive systems where reliability and error handling are non-negotiable

• Startup or high-growth technology background, particularly in technical leadership or ownership roles

Our comprehensive compensation package is designed to reward your expertise and includes both a competitive base salary and valuable stock options. Individual offers are determined based on a variety of factors, including your professional experience, core competencies, and geographic location.

Why Join Hippocratic AI

Reinvent healthcare with AI that puts safety first. We’re building the world’s first healthcare-only, safety-focused LLM — a breakthrough platform designed to transform patient outcomes at a global scale. This is category creation.

Work with the people shaping the future. Hippocratic AI was co-founded by CEO Munjal Shah and a team of physicians, hospital leaders, AI pioneers, and researchers from institutions like El Camino Health, Johns Hopkins, Washington University in St. Louis, Stanford, Google, Meta, Microsoft, and NVIDIA.

Backed by the world’s leading healthcare and AI investors. We recently raised a $126M Series C at a $3.5B valuation , led by Avenir Growth, bringing total funding to $404M with participation from CapitalG, General Catalyst, a16z, Kleiner Perkins, Premji Invest, UHS, Cincinnati Children’s, WellSpan Health, John Doerr, Rick Klausner, and others.

Build alongside the best in healthcare and AI. Join experts who’ve spent their careers improving care, advancing science, and building world-changing technologies — ensuring our platform is powerful, trusted, and truly transformative.