Lead the design and development of production AI systems powering insurance workflow automation.
Architect AI orchestration layers connecting LLMs, backend services, and business workflows.
Own end-to-end AI system design, including inference pipelines, routing, caching, and fallback strategies.
Drive engineering decisions around latency, reliability, cost, and scalability of AI services.
Lead implementation of observability systems (logging, monitoring, tracing, alerting).
Review and guide backend AI implementation across engineering teams.
Collaborate with product, backend, DevOps, and operations teams to ship end-to-end AI features.
Debug complex production issues across distributed AI systems and lead root-cause analysis.
Define engineering standards and best practices for AI system development.
Mentor engineers and elevate technical execution quality across teams.

Strong backend or AI engineering experience in production environments.
Experience building or scaling AI systems (LLMs, embeddings, recommendation systems, or automation workflows).
Strong system design skills with experience in distributed systems.
Experience with production inference pipelines and AI orchestration.
Strong debugging ability in high-scale, latency-sensitive environments.
Experience with observability, monitoring, and incident response.
Proven ability to lead technical execution in cross-functional teams.
Strong ownership mindset and ability to drive projects end-to-end.
Comfortable working in fast-paced, globally distributed teams.

Lead AI Engineer – AI Systems, Automation

Key skills