NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology—and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent. As an NVIDIAN, you'll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.
NVIDIA is looking for a Senior Staff Site Reliability Engineer to join our team in India. This is a senior individual-contributor role that combines real-time incident leadership with deep hands-on engineering, focused on how we detect, respond to, and prevent issues at scale across NVIDIA's AI-powered enterprise platforms. You will operate as an Incident Commander during critical events, set the technical direction for reliability engineering across multiple teams, and build the automation, observability, and AI-assisted tooling that reduce operational toil and raise reliability over time. You will also mentor and grow SRE talent as we scale the practice in India.
What You'll Be Doing:
Lead major incidents end to end — driving triage, cross-team coordination, decision making, and executive communication across global time zones.
Set technical direction for SRE initiatives that improve reliability, scalability, and developer efficiency across NVIDIA's enterprise systems, and drive them to adoption beyond your immediate team.
Design, build, and operate distributed systems — including Kubernetes-based and cloud-native infrastructure — that power NVIDIA's AI-powered enterprise products and services.
Build automation for incident detection, triage, communication, and remediation, replacing manual runbooks with self-healing systems.
Improve observability and signal quality to enable earlier detection, reduce alert noise, and eliminate reliance on user-reported issues.
Drive root cause analysis and translate learnings into systemic fixes, automation, and prevention mechanisms; raise the bar on post-incident review quality across the org.
Apply AI and data-driven techniques — LLMs, anomaly detection, signal correlation — to enhance incident triage, summarisation, and decision support.
Champion AI-assisted engineering practices, including coding agents and LLM-powered tooling, to accelerate day-to-day engineering workflows.
Partner with Cloud, Platform, Security, and AI/ML teams to embed SRE best practices, define SLOs and error budgets, and influence architecture early in the design cycle.
Mentor engineers, raise engineering standards through design and code review, and help build a strong reliability culture in the India organisation.
What We Need To See:
10+ years of experience in Site Reliability Engineering, Production Engineering, Platform Engineering, or Incident Management roles, with a track record of technical leadership at scale.
BS or MS degree in Computer Science, Engineering, or a related technical field (or equivalent practical experience).
Proven experience acting as an Incident Commander or leading major incident response in complex, high-availability environments.
Deep understanding of distributed systems, monitoring, and reliability engineering principles — SLIs/SLOs, error budgets, capacity planning, and graceful degradation.
Strong proficiency in at least one programming language (e.g., Python, Go, Java ) to build production-grade automation and tooling.
Hands-on expertise with public cloud platforms (AWS, Azure, or GCP) and container technologies such as Docker and Kubernetes.
Solid experience with infrastructure-as-code tooling (e.g., Terraform, AWS CDK, CloudFormation) and CI/CD pipelines.
Strong Linux/Unix and networking fundamentals, plus expertise in observability tooling such as OpenTelemetry, Prometheus, and Grafana.
Working knowledge of relational databases (e.g., PostgreSQL, MySQL) — SQL, indexing, and query optimisation.
Experience or familiarity with AI/ML concepts (e.g., LLMs, anomaly detection, or data-driven operations) applied to operational workflows.
Excellent written and verbal communication skills, with the ability to brief executives during high-pressure incidents and influence senior technical stakeholders.
Ways To Stand Out From The Crowd:
Building & applying AI to operations: Hands-on experience building incident management or automation platforms (ChatOps, workflow orchestration, alert intelligence) and applying AI to operations — intelligent triage, RCA generation, and signal correlation — with a demonstrable track record of reducing MTTD and MTTR, backed by numbers.
Scaling reliability across distributed teams: Proven ability to balance real-time incident leadership with scalable, long-term reliability solutions, including scaling a follow-the-sun model and operating AI/ML training and inference infrastructure at scale across multi-region teams.
Ownership & community impact: A strong sense of ownership, curiosity, and initiative — turning challenges into durable engineering solutions and diving into unfamiliar systems — along with contributions to open-source infrastructure/observability projects, conference talks, or active participation in the wider SRE community.
NVIDIA leads the charge in innovative breakthroughs in Artificial Intelligence, High-Performance Computing, and Visualization. The GPU, our invention, functions as the visual cortex of today's computers and forms the core of our products and services. Our work opens new realms to explore, encourages outstanding creativity and discovery, and powers inventions once thought of as science fiction — from artificial intelligence to autonomous systems. NVIDIA is searching for outstanding talent like you to help us advance the next wave of artificial intelligence!
Widely considered to be one of the technology world's most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family: www.nvidiabenefits.com
Skills Required
- 10+ years of experience in Site Reliability Engineering, Production Engineering, Platform Engineering, or Incident Management roles
- Technical leadership experience at scale
- Bachelor’s or master’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience
- Experience acting as an Incident Commander or leading major incident response in complex, high-availability environments
- Deep understanding of distributed systems, monitoring, and reliability engineering principles, including SLIs, SLOs, error budgets, capacity planning, and graceful degradation
- Strong proficiency in at least one programming language, such as Python, Go, or Java
- Hands-on expertise with public cloud platforms such as AWS, Azure, or GCP
- Experience with Docker and Kubernetes
- Experience with infrastructure-as-code tooling such as Terraform, AWS CDK, or CloudFormation
- Experience with CI/CD pipelines
- Strong Linux/Unix and networking fundamentals
- Expertise with observability tooling such as OpenTelemetry, Prometheus, and Grafana
- Working knowledge of relational databases, SQL, indexing, and query optimization
- Experience or familiarity with AI/ML concepts such as LLMs, anomaly detection, or data-driven operations applied to operational workflows
- Excellent written and verbal communication skills, including executive communication during high-pressure incidents
- Ability to influence senior technical stakeholders
- Hands-on experience building incident management or automation platforms and applying AI to operations
- Demonstrable record of reducing MTTD and MTTR with measurable results
- Experience scaling reliability across distributed teams and follow-the-sun operating models
- Experience operating AI/ML training and inference infrastructure at scale across multiple regions
- Contributions to open-source infrastructure or observability projects, conference talks, or active SRE community participation
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.
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Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
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.”
