About the role
Responsibilities:
- Build and lead a high-performing engineering team developing production Agentic AI systems.
- Own both delivery and technical outcomes: quality, reliability, latency and cost.
- Partner closely with Product, AI/Data Science and healthcare domain experts to turn complex workflows into reliable products.
- Drive architecture and design reviews across agents, backend services, tools and integrations.
- Establish evaluation as a core engineering discipline using golden datasets, measurable metrics, regression testing and release gates.
- Challenge technical decisions around prompts, models, tool design, orchestration, guardrails and agent architecture.
- Ensure production AI systems have strong observability, failure handling and incident-management practices.
- Hire exceptional engineers and create clear standards for engineering excellence.
- Coach and mentor engineers while maintaining a high bar for ownership and execution.
- Own production failures with the team and ensure learnings translate into better architecture, tooling and processes.
Requirements:
- 9+ years of engineering experience, including 2+ years directly managing engineers.
- Strong backend engineering foundation with experience owning production services before moving into management.
- Experience leading a team that has shipped LLM agents to real users in production for 1+ year.
- Strong system design and architecture fundamentals.
- Hands-on understanding of agent evaluation, including golden datasets, metrics and release gates.
- Ability to challenge technical decisions around model choice, agent architecture, reliability and cost.
- Experience hiring, mentoring and developing strong engineers.
- Strong product judgment and ability to work effectively across Product, Engineering, AI/Data Science and domain teams.