2 days ago
Base Salary
$272k - $431k/yr
Responsibilities
- Develop and deliver production-quality agentic AI systems using Python and/or Go, including Kubernetes deployment, agent runtimes, memory systems, orchestration, tool integration, and evaluation pipelines.
- Define NVIDIA’s enterprise agentic AI architecture through practical implementations, reference systems, and production deployments.
- Build multi-agent orchestration patterns using frameworks such as LangChain and LangGraph with regression coverage and observability.
- Prototype emerging agent architectures and harden successful approaches into reusable platform services, APIs, SDKs, and developer templates.
- Design data flywheels using telemetry, benchmarking, automated evaluation, and structured feedback loops to improve agent quality.
- Embed security, guardrails, sandbox isolation, auditability, and policy enforcement into agent runtimes.
- Evaluate and extend open-source and third-party agent platforms and make build-versus-use decisions.
- Collaborate with engineering, infrastructure, product, security, governance, and business stakeholders to drive enterprise adoption.
Requirements
- Bachelor’s degree in Computer Science or a related field or equivalent experience; a Master’s or PhD is preferred.
- 15+ years of experience building and shipping large-scale distributed systems with substantial hands-on coding in Python, Go, or similar systems languages.
- Demonstrated ability to progress from prototypes to robust, scalable platform solutions.
- Experience building agentic AI systems involving RAG pipelines, persistent memory, multi-agent management, tool frameworks, and evaluation infrastructure.
- Expertise in Kubernetes, containerized workloads, networking, APIs, and secure enterprise integration patterns.
- Experience building benchmarking, regression testing, telemetry, and observability systems measuring quality, latency, cost, reliability, and safety.
- Knowledge of performance tuning in hybrid environments, including GPU-based inference systems.
- Strong collaboration and communication skills for influencing technical and business audiences.
- Preferred experience with reusable SDKs, APIs, templates, reference implementations, CI/CD automation, enterprise vector databases, retrieval systems, Glean, Microsoft Copilot Studio, Google Agentspace, policy enforcement, access controls, sandbox isolation, audit trails, NVIDIA hardware optimization, and open-source contributions.
Benefits
- Eligible for equity and benefits.
- Expected base salary range is 272,000 USD–431,250 USD.
- Applications will be accepted at least until November 3, 2026.
- This posting is for an existing vacancy.
Tech Stack
Categories
About Nvidia
Nvidia designs and sells GPUs and accelerated computing platforms for data centers, AI/ML, graphics, gaming, and automotive, monetizing through hardware, software platforms (CUDA, AI frameworks), and systems like DGX and networking. Customers include cloud providers, enterprises, researchers, and OEMs. Founded in 1993 and headquartered in Santa Clara, it is a public company traded on NASDAQ under NVDA.