Overview:
In this role you will lead client-facing AI engineering in the health sector, shaping solution design and deployment. You’ll guide large, complex engagements from concept to delivery, translating clinical needs into AI requirements and roadmaps. You’ll design scalable AI components and support model readiness while driving adoption of AI-enabled capabilities across engagements. This position combines technical leadership with client advisory to deliver impactful, compliant health AI solutions. Compensation / Benefits medical, dental, vision 401k holiday pay vacation personal and family sick leave
Responsibilities:
Lead AI engineering workstreams from design to deployment for client engagements Translate clinical operations needs into AI requirements and delivery roadmaps Design retrieval, memory, prompt, and agent orchestration for scalable production use Oversee data wrangling, model integration, and software implementation on cloud platforms Evaluate model behavior using benchmarks and human review to ensure reliability Advise on platform choices, governance, portability, and workload fit across major AI platforms Coach teams to resolve blockers and raise technical decision quality across workstreams Communicate tradeoffs, dependencies, and delivery status to clients and internal leaders Develop LLMOps and AgentOps practices to improve observability and iterative refinement after launch Apply analytical thinking and data modeling to identify automation opportunities and cognitive solutions
Key requirements:
Bachelor degree at least 7 years of experience Coaching and mentoring teams Clear stakeholder communication Ability to translate clinical workflows into AI use cases GenAI/AI engineering in health systems RAG pipelines and agentic AI workflows MLOps platforms and governance in regulated environments
