Senior Staff Software Engineer - Agentic IT Operations

NVIDIA; United States; On-site; USD 200,000 - 320,000; Full time

Job summary

NVIDIA Corporation is seeking a Senior Staff Software Engineer to define the technical strategy for autonomous AI-driven enterprise operations. You will set the architecture that transforms IT from manual, reactive workflows into agentic platforms at global scale.

You will architect and build production systems using LLM-based agents, tool calling, RAG, and orchestration frameworks to deliver AI-assisted operations across employee support and IT services.

Qualifications

• Bachelor's or Master's degree in a related field, or equivalent experience.

Responsibilities

• Define the technical strategy and reference architecture for agentic AI across enterprise IT.
• Architect and build production agentic systems using LLM-based agents, tool calling, RAG, and orchestration frameworks.
• Design autonomous agents that execute complex, multi-step enterprise workflows with human-in-the-loop controls.

Skills

Infrastructure

SRE

DevOps

Platform

Production Engineering

Python

Go

Education

Bachelor's or Master's degree in related field

Tools

Kubernetes

Prometheus

Grafana

Datadog

PagerDuty

AWS

GCP

Azure

Job description

For over 25 years, NVIDIA has been at the forefront of transforming computer graphics, PC gaming, and accelerated computing, driven by a legacy of continuous innovation and exceptional talent. We are now leveraging the immense potential of AI to usher in the next era of computing, where our GPUs power the \"brains\" of computers, robots, and autonomous vehicles that can comprehend the world! This pioneering work demands vision, innovation, and the world's best talent. Join our diverse and supportive environment, where NVIDIANs are inspired to excel and make a profound global impact.

We are seeking a Senior Staff Software Engineer to define the technical strategy for autonomous AI-driven enterprise operations at NVIDIA. You will set the architecture that transforms IT from manual, reactive workflows into agentic platforms operating at global scale. This is senior individual contributor role on the team: you will own the hardest technical problems, establish the standards that other engineering organizations adopt, and be accountable for architectural decisions whose consequences compound for years. Exceptional interpersonal, written, and verbal communication skills are vital for success.

What You'll Be Doing:

As a Senior Staff Software Engineer, you will define how NVIDIA builds and operates autonomous enterprise systems. Your influence will be measured in systems adopted, engineers elevated, and problems that stopped being problems.

• Own the technical strategy and reference architecture for agentic AI across enterprise IT : agent runtimes, tool interfaces, memory and context management, orchestration, evaluation harnesses, and safety guardrails and establish them as the standard that partner engineering organizations build on.
• Architect and personally build production agentic systems using LLM-based agents, tool calling, RAG, and orchestration frameworks, delivering AI-assisted operations across employee support, endpoint services, and IT support operations.
• Design autonomous agents that execute complex, multi-step enterprise workflows end-to-end, coordinating approvals, vendor handoffs, cross-system data reconciliation, and exception handling with human-in-the-loop controls and own the reliability, observability, failure semantics, and blast-radius controls that make autonomy safe at enterprise scale.
• Own the architecture of the integration and automation platform spanning ServiceNow, ERP and procurement systems, and endpoint-management platforms, including infrastructure, data pipelines, APIs, and user-facing applications and make the build/buy/deprecate calls that shape it for the next several years.
• Define the engineering standards for how agentic systems are built, tested, evaluated, and operated: prompt and tool versioning, offline and online evals, regression suites, cost and latency budgets, security and data-governance patterns, and systematic failure-mode analysis.
• Drive technical alignment across organizational boundaries, partner engineering teams, platform owners, security, and senior leadership resolving contested architectural decisions and building consensus without formal authority.
• Multiply the organization. Mentor and grow senior and staff engineers through design partnership, code review, and technical coaching, and raise the engineering bar through the work you ship and the standards you enforce.

What We Need To See:

• Bachelor's or Master's degree in a related field, or equivalent experience. 12+ years of hands-on software engineering experience building and operating production systems at scale, with deep expertise in at least one of: Infrastructure, SRE, DevOps, Platform, or Production Engineering.
• Demonstrated impact at Senior Staff scope architectural decisions that shaped systems across multiple organizations, and a track record of being the person others escape to on the hardest technical problems.
• Deep expertise designing and shipping production software systems integrations, automation platforms, APIs, and data pipelines for complex enterprise operations at scale, with ownership spanning design through long-term operation.
• Proven experience taking agentic AI or LLM-based systems to production, including multi-step autonomous execution, tool calling, RAG, human-in-the-loop safeguards, exception handling, evaluation, and governance with measurable business outcomes.
• Track record of modernizing enterprise IT operations platforms (e.g., asset management, endpoint services, IT supply chain, infrastructure operations), including migrating or replacing entrenched legacy systems.
• Production-grade proficiency with infrastructure-as-code, CI/CD, containerization (Kubernetes), and cloud platforms (AWS, GCP, or Azure).
• Experience with monitoring and observability tools (Prometheus, Grafana, Datadog, PagerDuty, or similar).
• Fluent in Python, Go, or equivalent languages able to architect, write, and review production-quality code, not just scripts.
• Demonstrated