Responsibilities
- 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
Basic qualifications
- 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.
Preferred qualifications
- 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.
- 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. If anything
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