AI Engineer, Hippocratic AI

• 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
• 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
• 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

Desirable

• 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
• 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