Senior Staff Software Engineer - Agentic IT Operations

Reposted 4 Days Ago
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Santa Clara, CA, USA
In-Office
200K-322K Annually
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
Define the technical strategy and architecture for NVIDIA’s autonomous, AI-driven enterprise IT operations. Build production agentic systems using LLMs, tool calling, RAG, orchestration, and human-in-the-loop safeguards. Lead integration platforms across ServiceNow, ERP, procurement, and endpoint systems while establishing standards for reliability, evaluation, observability, security, and governance. Drive cross-organizational technical alignment, make major architecture decisions, mentor senior engineers, and scale adoption of agentic platforms.
Summary Generated by Built In

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.

Core responsibilities include:

  • 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 escalate 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 ability to grow other senior engineers and establish engineering practices that outlast your direct involvement.
  • Ability to drive technical direction across engineering, product, and senior leadership without formal authority, and to make complex trade-offs legible to VP and C-level audiences in business terms.

Ways To Stand Out From The Crowd:

  • Experience defining an agentic AI or automation platform strategy for a large enterprise and driving its adoption across multiple engineering organizations.
  • Built agent orchestration frameworks, eval infrastructure, or LLM observability tooling as internal platforms used by other teams.
  • Background designing event-driven or workflow-orchestration architectures (e.g., Temporal, Airflow, Kafka-based systems) for long-running, stateful enterprise processes at scale.
  • Deep working knowledge of ServiceNow or comparable ITSM/ERP platforms at the API and data-model level, including extending them in ways their vendors didn’t anticipate.
  • Open-source contributions, patents, published work, or conference talks in distributed systems, automation, or applied AI.

NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you’re creative and autonomous, we want to hear from you!

Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary range for this position is 200,000 USD – 322,000 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until November 3, 2026.

This posting is for an existing vacancy. 

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive 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.

Skills Required

  • 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
  • Deep expertise in Infrastructure, SRE, DevOps, Platform, or Production Engineering
  • Experience making architectural decisions at Senior Staff scope across multiple organizations
  • Experience designing and shipping production software systems, integrations, automation platforms, APIs, and data pipelines at scale
  • Production experience with agentic AI or LLM-based systems, including autonomous execution, tool calling, RAG, safeguards, exception handling, evaluation, and governance
  • Experience modernizing enterprise IT operations platforms, including asset management, endpoint services, IT supply chain, or infrastructure operations
  • Production-grade proficiency with infrastructure as code, CI/CD, containerization, Kubernetes, and a cloud platform such as AWS, GCP, or Azure
  • Experience with monitoring and observability tools such as Prometheus, Grafana, Datadog, or PagerDuty
  • Fluency in Python, Go, or equivalent programming languages
  • Ability to mentor senior engineers and establish durable engineering practices
  • Ability to drive technical direction across engineering, product, and senior leadership without formal authority
  • Experience defining enterprise agentic AI or automation platform strategies and driving adoption across engineering organizations
  • Experience building agent orchestration frameworks, evaluation infrastructure, or LLM observability tooling
  • Experience with event-driven or workflow-orchestration architectures such as Temporal, Airflow, or Kafka
  • Deep knowledge of ServiceNow or comparable ITSM or ERP platforms at the API and data-model level
  • Open-source contributions, patents, published work, or conference talks in distributed systems, automation, or applied AI

NVIDIA Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.

  • Equity Value & Accessibility — Company stock and RSUs have driven exceptional total compensation, with a generous employee stock purchase plan and ongoing equity refreshers playing a central role. Feedback suggests historic share-price gains created significant financial upside for many.
  • Healthcare Strength — Multiple plan options (HSA, PPO, and in some locations Kaiser) with in-network preventive care covered at 100% and company HSA contributions indicate a robust offering. Mental-health sessions and broad dental, vision, and disability coverage further strengthen the package.
  • Parental & Family Support — Up to 22 weeks of fully paid parental leave, adoption and surrogacy reimbursement, and coverage for IVF and egg freezing are highlighted as standout features. Additional family-care resources and caregiving support broaden the appeal.

NVIDIA Insights

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The Company
HQ: Santa Clara, CA
21,960 Employees
Year Founded: 1993

What We Do

NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”

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