Staff AI Engineer (Life Sciences)
About the role
As a Staff AI Engineer at Hippocratic AI, you'll set the technical direction for voice-based generative AI in healthcare. You'll architect 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 deeply influential role. You'll own one or more core AI domains end-to-end (RAG, agent orchestration, evaluation, or real-time voice) partnering with AI researchers, product managers, and clinical experts, and mentoring engineers across the org.
From designing the patterns other teams build on to bringing advanced language and speech models into production, your work will define how patients and providers safely interact with generative AI at scale.
Responsibilities
- Architect and own production-grade AI pipelines that power our voice-based generative healthcare agents
- RAG, multi-step reasoning, agent orchestration, and evaluation systems
- Making the foundational design decisions other teams build on
- Lead cross-functional initiatives with product, clinical, and engineering teams to translate healthcare workflows into safe, scalable, and human-centered AI experiences
- Represent engineering in high-stakes clinical and partner conversations
- Drive zero-to-one bets using state-of-the-art LLMs, retrieval systems, and streaming architectures
- Defining the problem, not just the solution
- Balancing innovation with reliability
- Own the safety and evaluation bar across model evaluation, safety testing, and observability
- Defining the gates every agent must clear before production
- Mentor senior and mid-level engineers, raise the quality bar through code review and design review, and multiply the impact of the teams around you
Requirements
- 6+ 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
Qualifications
- Must 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 is a plus