Senior Forward Deployed Engineer

Core Responsibilities
AI Innovation & Architecture – Design cutting-edge AI solutions to novel healthcare challenges; architect advanced RAG, tool-calling, and LLM technique approaches

Advanced RAG System Design – Design and implement advanced retrieval-augmented generation systems; optimize for relevance, latency, and cost; handle complex data sources and sophisticated chunking strategies

Advanced LLM Techniques – Apply sophisticated LLM engineering patterns (LLM-as-judge, multi-turn reasoning, complex prompt engineering); optimize agent behavior for production reliability

Proactive Customer Problem-Solving – Anticipate customer issues; propose proactive AI-driven solutions; identify optimization opportunities

Production Architecture & Operations – Design infrastructure for high-reliability AI systems; implement comprehensive monitoring, logging, and incident response; ensure systems meet production standards

Complex Deployments – Lead technical execution for sophisticated, novel deployments; own integration architecture; solve complex AI challenges creatively

Team Mentoring & Technical Leadership – Mentor junior FDEs on AI development and production patterns; contribute to technical standards and best practices

What You BringMust Haves
5-7 years of software engineering experience with expert-level Python and production software systems expertise

Advanced hands-on experience with LLM frameworks (LangChain, LangSmith); deep understanding of RAG, tool calling, and advanced LLM patterns; experience solving novel AI problems

Proven ability to architect and implement complex AI systems; experience designing systems for reliability and scale

Experience with sophisticated integrations and enterprise systems; strong understanding of systems reliability, error handling, and operational patterns.

Bachelor's degree in Computer Science or related field from a top ranked university.

Nice to Haves
Experience designing and optimizing advanced RAG systems at scale; deep knowledge of retrieval strategies, embedding models, or vector databases

Hands-on experience with Model Context Protocol (MCP) or similar sophisticated tool integration approaches

Healthcare IT experience (EHR integrations, FHIR, HL7, healthcare data standards)

Experience mentoring engineers or leading technical initiatives; contributions to AI/ML open source projects

Track record of driving innovation in AI systems or solving novel technical challenges

Why Hippocratic AI
You're architecting the future of AI in healthcare. You're designing sophisticated systems that solve cutting-edge healthcare AI challenges. Your RAG architectures, tool-calling patterns, advanced LLM techniques, and production systems directly transform healthcare operations at scale. This is architectural-level impact on healthcare innovation.

You work with world-class AI engineers and clinical experts. The team includes AI pioneers from Google, Meta, Microsoft, NVIDIA and clinical leaders from Johns Hopkins, Washington University, Stanford. You'll tackle the hardest AI innovation problems with the sharpest minds. You'll grow faster here than almost anywhere.

Backed by $404M from top-tier AI and healthcare investors—CapitalG, a16z, General Catalyst, plus health system validators like UHS, Cincinnati Children's, WellSpan. You're not betting on unproven ideas; you're building on validated market demand and deep institutional support. Focus on technical excellence at scale.

This is category creation in AI-native healthcare delivery. You're defining how LLM agents interact with healthcare systems, how sophisticated RAG enables clinical AI, how to deploy advanced AI techniques safely. You're writing the playbooks. Every system you build contributes to transforming how healthcare uses AI.

Skills Required
5-7 years of software engineering experience
Expert-level Python
Production software systems expertise
Hands-on experience with LLM frameworks (LangChain, LangSmith)
Deep understanding of RAG, tool calling, and advanced LLM patterns
Proven ability to architect and implement complex AI systems for reliability and scale
Experience with sophisticated integrations and enterprise systems; strong systems reliability and error handling knowledge
Bachelor's degree in Computer Science or related field from a top ranked university
Experience designing and optimizing advanced RAG systems at scale; knowledge of retrieval strategies, embedding models, or vector databases
Hands-on experience with Model Context Protocol (MCP) or similar tool integration approaches
Healthcare IT experience (EHR integrations, FHIR, HL7, healthcare data standards)
Experience mentoring engineers or leading technical initiatives; contributions to AI/ML open source projects
Track record of driving innovation in AI systems or solving novel technical challenges