Lead Principal Engineer, Enterprise Agentic AI Platform

What you'll do

• Develop end-to-end agent systems, runtimes, orchestration, memory, integrations, and evaluation pipelines.
• Define architecture through production deployments, reference implementations, reusable platform services, APIs, SDKs, and templates.
• Implement agent quality data flywheels and embed security, guardrails, isolation, auditability, and policy enforcement.

What they ask for

• 15+ years building and shipping large-scale distributed systems with significant hands-on coding in Python, Go, or similar systems languages.
• Proven experience constructing agentic AI systems, including RAG, persistent memory, multi-agent management, tool frameworks, and evaluation infrastructure.
• Expert-level depth in Kubernetes, containerized workloads, networking, APIs, and secure enterprise integration patterns.
• Experience with benchmarking, regression testing, telemetry, observability, and performance tuning in hybrid environments, including GPU-based inference systems.

Nice to have

• Master’s or PhD.
• Experience with reusable developer components, enterprise vector databases or agent platforms, runtime policy enforcement, GPU optimization, or meaningful open-source contributions.

Pay

272,000 USD - 431,250 USD (base salary)

Tools

Python, Go, Kubernetes, LangChain, LangGraph, Cursor, Claude Code, Claude Cowork

AI focus

Build enterprise agentic AI platforms and production agents, including multi-agent orchestration, memory, RAG, evaluation, telemetry-driven improvement, GPU inference, and secure runtime controls.