Lead Principal Engineer, Enterprise Agentic AI Platform

What you'll do

• Develop and deliver production-quality agentic AI systems from start to finish using Python and/or Go.
• Build multi-agent orchestration patterns including planner, executor, reviewer, and tool agents using frameworks like LangChain or LangGraph.
• Create and harden functional prototypes into reusable platform services, APIs, SDKs, and developer templates.
• Architect and implement data flywheels for continuous agent improvement through telemetry, benchmarking, and automated evaluation.
• Embed security guardrails, sandbox isolation, and auditability directly into agent runtimes.
• Evaluate and integrate open-source and third-party agent platforms based on performance and scalability.
• Optimize model inference and memory utilization for GPU-powered performance in hybrid environments.

What we're looking for

• Bachelor’s degree in Computer Science or related field or equivalent experience.
• Master’s or PhD preferred.
• 15+ years of experience building and shipping large-scale distributed systems with significant hands-on coding in Python, Go, or similar systems languages.
• Proven track record in constructing agentic AI systems, including RAG pipelines, long-lasting memory models, multi-agent management, and evaluation infrastructure.
• Expert-level depth in Kubernetes, containerized workloads, networking, APIs, and secure enterprise integration patterns.
• Comprehensive knowledge of performance tuning in hybrid environments, including GPU-based inference systems.
• Experience crafting benchmarking, regression testing, telemetry, and observability systems to measure agent quality, latency, cost, reliability, and safety.
• Experience delivering reusable developer-acceleration components such as SDKs, APIs, templates, and CI/CD automation (preferred).