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

• 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.

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.

About the Role

As a Senior Backend LLM Engineer at Hippocratic AI, you will play a key role in building the core infrastructure that powers our AI-driven healthcare products. You’ll join a collaborative team of engineers, applied scientists, and healthcare professionals working at the intersection of Generative AI and clinical workflows. Your work will focus on designing, developing, and scaling backend systems that ensure our products are safe, reliable, and ready for high-stakes use in healthcare environments.

This role is deeply cross-functional—you will work closely with ML engineers, data scientists, product managers, designers, and clinical experts to transform complex requirements into secure, high-performance backend services. From data processing pipelines to API design and system reliability, your contributions will directly shape how patients and providers interact with next-generation AI systems.

We’re looking for engineers who are passionate about innovation, thrive in fast-paced environments, and want to build real-world healthcare solutions with cutting-edge AI technologies.

What You'll Do

• Develop and maintain scalable backend systems for high-performance AI applications in healthcare.
• Collaborate with ML engineers and data scientists to design and build efficient pipelines for large-scale healthcare datasets.
• Build and manage APIs and microservices that enable data retrieval, processing, and interaction with AI models.
• Implement strong data security, privacy, and compliance practices for sensitive patient data.
• Monitor, debug, and optimize backend systems for performance, reliability, and uptime.
• Translate healthcare and product requirements into architectures and technical solutions.

What You Bring

Must Have:

• Bachelor’s degree in Computer Science, Engineering, or equivalent experience.
• 5+ years of backend development experience using Python, Go, or similar languages.
• Familiarity with SaaS control planes, relational databases, and RESTful APIs.
• Strong understanding of cloud infrastructure (AWS, GCP, Kubernetes, S3).
• Proven ability to architect scalable systems and deliver high-quality, production-grade code.

If you’re an engineer passionate about building high scale AI-powered experiences and ready to work on cutting-edge B2B products that make a real impact in healthcare, we’d love to hear from you.

Join our team at Hippocratic AI and help shape the future of clinically safe, production-grade AI systems