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.

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.

About The Role As an AI Engineer at Hippocratic AI , you’ll play a pivotal role in shaping the future of voice-based generative AI in healthcare . You’ll design and build the intelligent systems that power our clinically safe healthcare agents , working at the intersection of large language models, real-time voice, and human-centered product design.

This is a deeply hands-on and cross-functional role , partnering closely with AI researchers, product managers, and clinical experts to bring advanced language and speech models into production. From building scalable RAG and multi-agent pipelines to conversational interactions, your work will directly influence how patients and providers safely interact with generative AI at scale.

We’re looking for experienced engineers who are passionate about AI in the real world —people who love taking cutting-edge research, turning it into robust products, and advancing the frontier of what’s possible in safe, agentic healthcare systems .

What You'll Do:

• Design, build, and optimize production-grade AI pipelines that power our voice-based generative healthcare agents—from retrieval-augmented generation (RAG) to multi-step reasoning systems.
• Collaborate cross-functionally with product, clinical, and engineering teams to translate healthcare workflows into safe, scalable, and human-centered AI experiences.
• Prototype and deploy zero-to-one features using state-of-the-art LLMs, retrieval systems, and streaming architectures—balancing innovation with reliability.
• Develop and refine AI-native workflows that support real-time, conversational, and long-running interactions across diverse healthcare contexts.
• Drive continuous improvement in model evaluation, safety testing, and observability, ensuring every agent interaction meets clinical safety standards

What You Bring

Must Have:

• 3+ years of professional experience in software, ML, or AI engineering.
• Proven track record building and shipping AI- or ML-powered products in production environments.
• Strong programming skills in Python with experience in distributed systems, APIs, and data pipelines.
• Deep understanding of prompt engineering, vector databases, and retrieval systems (RAG), voice agents or willingness to learn rapidly.
• Experience with cloud environments (AWS/GCP/Azure) and modern DevOps practices (Terraform, CI/CD, monitoring).
• Excellent communication, cross-functional collaboration, and an ability to move fast in high-impact domains.

Nice-to-Have:

• Experience building or deploying LLM-based or multi-agent systems at scale.
• Hands-on work with speech recognition, text-to-speech, or streaming architectures for real-time AI experiences.
• Prior exposure to healthcare, safety-critical domains, or regulated product development.

If you’re an AI engineer who thrives at the intersection of cutting-edge research and real-world product impact , we’d love to hear from you.

Join Hippocratic AI and help shape the future of clinically safe, voice-enabled AI systems that are already transforming patient care at scale.

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.