
Forward Deployment Engineer (Residency Program)
Menlo Park, CA at a glance
- Rent
- #2 of 51$3,490/mo+46% vs US avg
- Weather
- #17 of 51292 mild days0 hot · 0 cold
- Income tax
- #1 of 5113.3% top rateCalifornia
What you need
- 2+ yrs software development or AI/ML experience
- Strong Python proficiency with production code
- Demonstrated LLM prompting experience (ChatGPT, Claude)
- Experience building REST API and database integrations
- Bachelor's degree in CS or equivalent experience
What you'll do
- Develop advanced prompts for clinical conversation planning layer
- Engineer conversation logic balancing clinical accuracy, safety, patient experience
- Build integrations connecting agents to EHRs, scheduling, telephony platforms
- Collaborate with clinicians to translate requirements into conversation designs
- Conduct experiments on model outputs and prompt variations
Role Mission
As HAI's Forward Deployed Engineer (FDE) Resident, you will own the delivery of safe, autonomous clinical conversations with patients, from the conversation layer to the integration design. You'll develop and refine the prompts and conversation logic that determine how millions of patients experience our breakthrough healthcare AI. And you’ll architect the transports and mappings to get data in and out of these conversations. This role exists because building truly autonomous clinical conversations requires both deep technical skill and relentless focus on patient experience—and we need someone who can master both.
What You Will Accomplish
Own your first major outcome: By day 90, you will have shipped improvements to at least two live conversation workflows, developed advanced prompts that meaningfully improve clinical safety scores or patient satisfaction metrics, collaborated with clinicians to translate their feedback into conversation logic, and shipped code that's now running in production healthcare environments.
Drive lasting impact: This is the front door to our Forward Deployed Engineer (FDE) track: your first 6 months are as an FDE Resident, followed by 6 months as an Associate FDE, working alongside FDE leadership with exposure to Product Engineering and AI Engineering along the way. Most residents graduate into full FDE roles, with some moving into Engineering or Product based on their strengths and interests.
The Team
You'll work alongside software engineers, ML scientists, product managers, and clinical experts who are obsessed with getting conversation right. This is a collaborative team that ships fast, values experimentation, and treats patient safety as non-negotiable. You'll have direct input into product decisions and the autonomy to innovate on conversation and integration design.
What You Will Do
Develop advanced prompts for our conversation planning layer using sophisticated prompting techniques (chain-of-thought, few-shot learning, role-based prompting, structured outputs) to enable complex agentic workflows that handle real clinical scenarios
Engineer conversation logic and patient interactions that balance clinical accuracy, safety guardrails, and patient experience—writing, testing, and iterating on prompts that make our agents feel natural and trustworthy
Design and build the integrations that connect our conversational agents to customer EHRs, scheduling systems, and telephony platforms—turning HL7/FHIR feeds and REST/webhook APIs into the real-time signals that shape every conversation
Collaborate with clinicians, product managers, and engineers to translate clinical requirements into conversation designs, conduct user testing with healthcare professionals, and iterate based on feedback from real-world usage
Conduct rigorous experiments and analysis on model outputs, prompt variations, and conversation strategies—measuring impact on clinical safety scores, patient satisfaction, task completion rates, and other key metrics
Use advanced prompting techniques including retrieval augmentation, tool calling, conditional logic, and multi-turn conversation management to optimize model performance and patient experience across diverse clinical scenarios
Maintain and improve our conversation codebase, ensuring prompts are version-controlled, documented, and deployed safely to production healthcare environments with proper testing and rollout procedures
Sit shoulder-to-shoulder with customer engineering teams during go-lives, debugging integration issues live and turning one partner's edge case into a reusable pattern that ships to every future customer
Location Requirement
We believe the best ideas happen together. To support fast collaboration and a strong team culture, this role is expected to be in our Palo Alto office five days a week, unless otherwise specified.
Basic Qualifications
Bachelor's degree in Computer Science, Computer Engineering, Software Engineering, or a related technical field (or equivalent demonstrated coursework and professional projects)
2+ years of professional industry experience in software development, AI/ML, or related technical roles
Strong Python proficiency with hands-on experience writing production or near-production code
Demonstrated experience with LLM prompting through professional work or substantial personal projects (ChatGPT, Claude, or similar models)
Experience building integrations with databases and RESTful APIs, including understanding of async patterns and error handling
Strong problem-solving mindset with proven ability to break down complex problems and iterate toward solutions
Preferred Qualifications
Experience with backend development frameworks (Flask, Django, FastAPI, Spring Boot, or similar)
Portfolio of personal or academic projects demonstrating full-stack development, AI experimentation, or prompt engineering work
Familiarity with AI/ML concepts including model architectures, training approaches, or evaluation methods
Understanding of data privacy, security, and compliance best practices, particularly in regulated healthcare environments (HIPAA, healthcare data handling)
Healthcare or health-tech experience, including exposure to clinical workflows, EHR systems, or patient-facing applications
Experience with prompt engineering frameworks or tools (LangChain, LangSmith, Anthropic SDK, etc.)
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.
Equal Opportunity
Hippocratic AI is an equal opportunity employer. We do not discriminate on the basis of race, color, religion, national origin, sex, age, disability, sexual orientation, gender identity or expression, genetic information, military or veteran status, or any other characteristic protected by applicable law. We are committed to building a team that reflects the patients we serve. We actively encourage applications from candidates of all backgrounds. If you require accommodations during the hiring process, please contact [email protected].
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.
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About Hippocratic AI
Hippocratic AI has developed a safety-focused Large Language Model (LLM) for healthcare. The company believes that a safe LLM can dramatically improve healthcare accessibility and health outcomes in the world by bringing deep healthcare expertise to every human. No other technology has the potential to have this level of global impact on health. The company was co-founded by CEO Munjal Shah, alongside a group of physicians, hospital administrators, healthcare professionals, and artificial intelligence researchers from El Camino Health, Johns Hopkins, Stanford, Microsoft, Google, and NVIDIA. Hippocratic AI has received a total of $278 million in funding and is backed by leading investors, including Andreessen Horowitz, General Catalyst, Kleiner Perkins, NVIDIA’s NVentures, Premji Invest, SV Angel, and six health systems. For more information on Hippocratic AI, www.HippocraticAI.com. 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. If anything appears suspicious, stop engaging immediately and report the incident.
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