Hippocratic AI
Agent Deployment Engineer (Residency Program)
Hippocratic AI, Palo Alto, California, United States, 94306
About Us
Hippocratic AI is developing the first safety-focused Large Language Model (LLM) for healthcare. Our mission is to dramatically improve healthcare accessibility and outcomes by bringing deep healthcare expertise to every person. No other technology has the potential for this level of global impact on health. Why Join Our Team:
Innovative mission:
We are creating a safe, healthcare-focused LLM that can transform health outcomes on a global scale.
Visionary leadership:
Hippocratic AI was co-founded by CEO Munjal Shah alongside physicians, hospital administrators, healthcare professionals, and AI researchers from top institutions including El Camino Health, Johns Hopkins, Washington University in St. Louis, Stanford, Google, Meta, Microsoft and NVIDIA.
Strategic investors:
We have raised a total of $278 million in funding, backed by top investors such as Andreessen Horowitz, General Catalyst, Kleiner Perkins, NVIDIA’s NVentures, Premji Invest, SV Angel, and six health systems.
Team and expertise:
We are working with top experts in healthcare and artificial intelligence to ensure the safety and efficacy of our technology. For more information, visit www.HippocraticAI.com. We value in-person teamwork and believe the best ideas happen together. Our team is expected to be in the office five days a week in Palo Alto, CA unless explicitly noted otherwise in the job description.
About the Role
Join Hippocratic AI’s Agent Deployment Engineering Residency as a Junior Agent Deployment Engineer. You’ll help build and tune the conversation layer that powers safe, fully autonomous clinical dialogues—combining Python-driven tooling with advanced prompting to orchestrate agentic workflows. This is an on-site role in Palo Alto, CA, with an initial 3-month term, $55/hour, and top performers will be offered extensions or full-time roles. What You’ll Do
Design, implement, and iterate prompting strategies within our state-of-the-art conversation planning layer to enable end-to-end agentic workflows.
Partner with Product, Engineering, Model, and Deployment Architecture teams to deliver autonomous, patient-oriented clinical conversations that meet safety and quality bars.
Author and maintain reusable prompt patterns, guards, and fallbacks to improve reliability, clinical safety, and user experience.
Run targeted experiments (A/Bs and offline evals), analyze outputs, and use findings to optimize prompts, flows, and tooling.
Contribute lightweight Python utilities and configs that instrument, evaluate, and ship agents quickly and safely.
What We’re Looking For (Must-Have)
Bachelor’s in Computer Science, Computer Engineering, or related field (or equivalent coursework/projects).
Proficiency with Python and comfort building small tools/CLI scripts.
Hands-on LLM prompting experience (e.g., ChatGPT, Claude) in professional or personal projects.
Strong problem-solving skills and a willingness to learn in a fast-moving environment.
Nice-to-Have (But Not Required)
Backend project experience (personal, academic, or internship).
Exposure to databases and RESTful APIs.
Foundational understanding of AI/ML concepts—or a strong desire to learn.
Familiarity with modern web frameworks (e.g., Flask, Django, or Spring Boot).
Awareness of data privacy and security best practices in regulated settings (healthcare a plus).
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Hippocratic AI is developing the first safety-focused Large Language Model (LLM) for healthcare. Our mission is to dramatically improve healthcare accessibility and outcomes by bringing deep healthcare expertise to every person. No other technology has the potential for this level of global impact on health. Why Join Our Team:
Innovative mission:
We are creating a safe, healthcare-focused LLM that can transform health outcomes on a global scale.
Visionary leadership:
Hippocratic AI was co-founded by CEO Munjal Shah alongside physicians, hospital administrators, healthcare professionals, and AI researchers from top institutions including El Camino Health, Johns Hopkins, Washington University in St. Louis, Stanford, Google, Meta, Microsoft and NVIDIA.
Strategic investors:
We have raised a total of $278 million in funding, backed by top investors such as Andreessen Horowitz, General Catalyst, Kleiner Perkins, NVIDIA’s NVentures, Premji Invest, SV Angel, and six health systems.
Team and expertise:
We are working with top experts in healthcare and artificial intelligence to ensure the safety and efficacy of our technology. For more information, visit www.HippocraticAI.com. We value in-person teamwork and believe the best ideas happen together. Our team is expected to be in the office five days a week in Palo Alto, CA unless explicitly noted otherwise in the job description.
About the Role
Join Hippocratic AI’s Agent Deployment Engineering Residency as a Junior Agent Deployment Engineer. You’ll help build and tune the conversation layer that powers safe, fully autonomous clinical dialogues—combining Python-driven tooling with advanced prompting to orchestrate agentic workflows. This is an on-site role in Palo Alto, CA, with an initial 3-month term, $55/hour, and top performers will be offered extensions or full-time roles. What You’ll Do
Design, implement, and iterate prompting strategies within our state-of-the-art conversation planning layer to enable end-to-end agentic workflows.
Partner with Product, Engineering, Model, and Deployment Architecture teams to deliver autonomous, patient-oriented clinical conversations that meet safety and quality bars.
Author and maintain reusable prompt patterns, guards, and fallbacks to improve reliability, clinical safety, and user experience.
Run targeted experiments (A/Bs and offline evals), analyze outputs, and use findings to optimize prompts, flows, and tooling.
Contribute lightweight Python utilities and configs that instrument, evaluate, and ship agents quickly and safely.
What We’re Looking For (Must-Have)
Bachelor’s in Computer Science, Computer Engineering, or related field (or equivalent coursework/projects).
Proficiency with Python and comfort building small tools/CLI scripts.
Hands-on LLM prompting experience (e.g., ChatGPT, Claude) in professional or personal projects.
Strong problem-solving skills and a willingness to learn in a fast-moving environment.
Nice-to-Have (But Not Required)
Backend project experience (personal, academic, or internship).
Exposure to databases and RESTful APIs.
Foundational understanding of AI/ML concepts—or a strong desire to learn.
Familiarity with modern web frameworks (e.g., Flask, Django, or Spring Boot).
Awareness of data privacy and security best practices in regulated settings (healthcare a plus).
#J-18808-Ljbffr