- Location
- Santa Clara, CA,US, US
- Type
- Full-time
- Department
- Engineering
- Seniority
- Lead
- Source
- Eightfold
Description
Architecture authority is earned through production systems, measurable impact, and technical depth. 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. 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. Architect and implement data flywheels that continuously improve agent quality through telemetry, benchmarking, automated evaluation, and structured feedback loops. 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. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 272,000 USD - 431,250 USD. You will also be eligible for equity and benefits. Applications for this job will be accepted at least until March 2, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law. Experience crafting benchmarking, regression testing, telemetry, and observability systems that measure agent quality, latency, cost, reliability, and safety. Experience integrating enterprise vector databases and retrieval systems, and working with agentic search and orchestration platforms such as Glean, Microsoft Copilot Studio, Google Agentspace, or similar enterprise AI ecosystems. Experience embedding fine-grained policy enforcement, access controls, sandbox isolation, and audit trails directly into AI runtimes.
