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Lead Principal Engineer, Enterprise Agentic AI Platform

NVIDIA· Engineer, Sys SW
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Santa Clara, CA$272k - $431.3kfull-timePosted 7mo ago

About the role

Lead architect and hands-on engineer to define and build NVIDIA’s Enterprise Agentic AI Platform, delivering production-grade, enterprise-ready agentic AI systems with strong governance, security, and observability. Role requires deep technical leadership, daily coding in Python and/or Go, and end-to-end system delivery from concept to production.

Responsibilities

  • Develop and deliver production-quality agentic AI systems from start to finish using Python and/or Go, covering Kubernetes deployment, agent runtimes, memory systems, orchestration, tool integration, and evaluation pipelines.
  • Define and advance NVIDIA’s Enterprise Agentic AI architecture through practical implementations, reference systems, and production deployments—not abstract diagrams.
  • Build and implement multi-agent orchestration patterns (planner, executor, reviewer, tool agents) using frameworks such as LangChain, LangGraph, or similar orchestration systems, with strong regression coverage and observability.
  • Run fast, high-quality POCs on emerging agent architectures; harden successful patterns into reusable platform services, APIs, SDKs, and developer templates.
  • Architect and implement data flywheels that continuously improve agent quality through telemetry, benchmarking, automated evaluation, and structured feedback loops.
  • Embed security, guardrails, sandbox isolation, auditability, and policy enforcement directly into agent runtimes in partnership with security and governance teams.
  • Evaluate, integrate, and extend open-source and third-party agent platforms; drive disciplined build-vs-use decisions based on performance, scalability, control, and long-term platform ownership.
  • Collaborate closely with engineering, infrastructure, product, and business collaborators to align architectural direction with enterprise priorities and accelerate adoption.

Qualifications

  • 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 skill in quickly transitioning from an idea to a functional prototype and then to a robust, scalable platform solution.
  • Proven track record in constructing agentic AI systems, including RAG pipelines, long-lasting memory models, multi-agent management (e.g., LangChain, LangGraph), tool frameworks, and evaluation infrastructure.
  • Expert-level depth in Kubernetes, containerized workloads, networking, APIs, and secure enterprise integration patterns.
  • Experience crafting benchmarking, regression testing, telemetry, and observability systems that measure agent quality, latency, cost, reliability, and safety.
  • Comprehensive knowledge of performance tuning in hybrid environments, including GPU-based inference systems.
  • Excellent collaboration skills with the ability to influence cross-functional collaborators, build positive relationships, and clearly communicate complex architectural concepts to both technical and business audiences.

Skills

Required:PythonGoKubernetesAgentic AI architectures (RAG, multi-agent systems)Security and governance integration

Benefits

  • equity
  • benefits (see NVIDIA benefits)
Last updated Jul 3, 2026. Interested? Apply on the company site.

About NVIDIA

World Leader in AI Computing

NVIDIA invents the GPU and drives advances in AI, HPC, gaming, creative design, autonomous vehicles, and robotics.

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