Senior Staff Software Engineer - Agentic IT Operations

NVIDIA•Santa Clara, CA

1d•$200,000 - $322,000

About The Position

NVIDIA is seeking a Senior Staff Software Engineer to define the technical strategy and architecture for autonomous, AI-driven enterprise operations. This senior individual contributor will own difficult technical problems, establish standards adopted by other engineering organizations, and make architectural decisions with long-term impact. Success requires strong interpersonal, written, and verbal communication skills. The role focuses on building and operating agentic enterprise systems that move IT from manual, reactive workflows toward globally scalable autonomous platforms. The engineer will shape agent runtimes, tool interfaces, memory and context management, orchestration, evaluation, safety, and integrations across enterprise IT systems. They will also influence teams across organizational boundaries and mentor senior and staff engineers. The position requires 12+ years of hands-on software engineering experience building and operating production systems at scale, with deep expertise in infrastructure, SRE, DevOps, platform, or production engineering. Candidates should have experience delivering production agentic AI or LLM systems, enterprise integrations and automation platforms, and production-quality software. A bachelor's or master's degree in a related field, or equivalent experience, is required. The base salary range is USD 200,000–322,000, determined by location, experience, and compensation of employees in similar positions. The role is also eligible for equity and benefits. Applications will be accepted at least until November 2, 2026. The posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes and is an equal opportunity employer.

Requirements

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 at least one of Infrastructure, SRE, DevOps, Platform, or Production Engineering.
Demonstrated impact at Senior Staff scope, including architectural decisions shaping systems across multiple organizations and a record of addressing 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 from 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.
Experience modernizing enterprise IT operations platforms, such as asset management, endpoint services, IT supply chain, or infrastructure operations, including migrating or replacing legacy systems.
Production-grade proficiency with infrastructure-as-code, CI/CD, containerization such as Kubernetes, and a cloud platform such as AWS, GCP, or Azure.
Experience with monitoring and observability tools such as Prometheus, Grafana, Datadog, PagerDuty, or similar.
Fluency in Python, Go, or equivalent languages, with the ability to architect, write, and review production-quality code.
Demonstrated ability to grow other senior engineers and establish engineering practices that outlast direct involvement.
Ability to drive technical direction across engineering, product, and senior leadership without formal authority, and explain complex trade-offs to VP- and C-level audiences in business terms.
Exceptional interpersonal, written, and verbal communication skills.

Nice To Haves

Experience defining an agentic AI or automation platform strategy for a large enterprise and driving adoption across multiple engineering organizations.
Experience building agent orchestration frameworks, evaluation infrastructure, or LLM observability tooling as internal platforms used by other teams.
Background designing event-driven or workflow-orchestration architectures, such as Temporal, Airflow, or 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 beyond anticipated vendor use cases.
Open-source contributions, patents, published work, or conference talks in distributed systems, automation, or applied AI.

Responsibilities

Own the technical strategy and reference architecture for agentic AI across enterprise IT, including agent runtimes, tool interfaces, memory and context management, orchestration, evaluation harnesses, and safety guardrails.
Architect and build production agentic systems using LLM-based agents, tool calling, retrieval-augmented generation (RAG), and orchestration frameworks for employee support, endpoint services, and IT support operations.
Design autonomous agents for complex, multi-step enterprise workflows, with approval coordination, vendor handoffs, cross-system data reconciliation, exception handling, and human-in-the-loop controls.
Own reliability, observability, failure semantics, and blast-radius controls for safe enterprise-scale autonomy.
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.
Make build, buy, and deprecate decisions that shape the integration and automation platform over the coming years.
Define engineering standards for building, testing, evaluating, and operating agentic systems, including versioning, evaluations, regression suites, cost and latency budgets, security, data governance, and failure-mode analysis.
Drive technical alignment among partner engineering teams, platform owners, security, and senior leadership, resolving architectural disagreements and building consensus without formal authority.
Mentor and grow senior and staff engineers through design partnership, code review, and technical coaching.
Raise engineering standards through shipped work and practices that endure beyond direct involvement.