Level

NVIDIA

Engineering Manager – AI Platform & SRE

AI in this role

Engineering Manager leading an SRE and platform team responsible for building and operating resilient AI platforms and agents.

kubernetesinfrastructure-as-code
ai-agentsai-automationsredistributed-systemsengineering-managementai-platformsautomation

Site Reliability Engineering (SRE) at NVIDIA is an engineering field focused on designing, building, and operating large-scale production systems with exceptional reliability, efficiency, and availability. It combines software and systems engineering practices with expertise across distributed systems, networking, Kubernetes, public cloud, observability, capacity management, continuous delivery, and automation.


As an Engineering Manager, you will lead a team of dedicated engineers responsible for building and operating resilient AI platform capabilities at enterprise scale. You will combine people leadership with strong technical judgment, helping the team translate ambiguous business and engineering challenges into a clear strategy and executable roadmap. You will partner across Cloud, Platform, Security, and AI/ML organizations to deliver reliable systems, improve developer productivity, and advance the use of AI agents and skills in platform operations.


Our culture values diversity, intellectual curiosity, collaboration, and continuous learning. We encourage thoughtful risk-taking, blameless analysis, and shared ownership. You will create an environment in which engineers can do their best work, grow their careers, and make a meaningful impact.


What you’ll be doing

  • Lead, develop, and grow a team of SRE, platform, and software engineers responsible for NVIDIA’s AI Platform Runtime and related production services.
  • Define the team’s technical strategy, priorities, and roadmap in alignment with broader product, platform, and business objectives.
  • Guide the design and delivery of highly available, scalable, secure, and resilient distributed systems that support enterprise AI agent products.
  • Drive the development of AI agents, AI skills, and intelligent automation for platform operations, incident response, troubleshooting, and remediation.
  • Establish measurable reliability goals and effective operational practices using service-level indicators, service-level objectives, error budgets, capacity models, operational health metrics, and production readiness reviews.
  • Improve engineering velocity and developer experience through self-service platforms, infrastructure-as-code, standardized delivery patterns, and automation.
  • Partner with product managers, architects, and leaders across Cloud, Security, Networking, Platform, and AI/ML teams to coordinate initiatives involving multiple functions.
  • Maintain a healthy balance among feature delivery, platform investment, operational work, reliability improvements, and technical debt reduction.
  • Lead the team through critical incidents and ensure that blameless postmortems result in clear ownership and durable corrective actions.
  • Recruit exceptional engineers and foster an inclusive, high-performing environment through coaching, feedback, career development, and thoughtful delegation.

What we need to see

  • 10+ years of experience in Site Reliability Engineering, Platform Engineering, Software Engineering, Cloud Infrastructure, or a related technical field, including 3+ years managing or formally leading engineering teams responsible for complex production systems.
  • Technical foundation in distributed systems, Linux, networking, Kubernetes, and public cloud platforms such as AWS, Azure, or GCP.
  • Experience leading teams that build production software and automation using languages such as Python, Go, TypeScript, JavaScript, or Java.
  • Solid understanding of observability at scale, including OpenTelemetry, metrics, logs, distributed tracing, profiling, and operational analytics.
  • Experience applying SRE practices such as service-level objectives, error budgets, capacity and resource management, incident management, disaster recovery, and blameless postmortems.
  • Demonstrated ability to create technical roadmaps, manage competing priorities, and deliver measurable outcomes across multiple teams.
  • Proven ability to hire, coach, retain, and develop engineers at different career stages.
  • Outstanding communication and collaboration skills, with the ability to influence across technical, product, and organizational boundaries.

Ways to stand out from the crowd

  • Hands-on experience with AI agents, agentic workflows, or intelligent automation for infrastructure and production operations.
  • A track record of improving availability, performance, operational efficiency, developer productivity, or incident response through measurable engineering initiatives.
  • Experience building or scaling an SRE or platform engineering function across a large enterprise and coordinating complex programs across organizational boundaries.
  • Success developing senior engineers and technical leaders, paired with a strong sense of ownership, curiosity, and empathy that enables you to build trust and bring clarity to ambiguity.

NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing, and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens new universes to explore, enables outstanding creativity and discovery, and powers innovations that were once science fiction, from artificial intelligence to autonomous vehicles.


NVIDIA is looking for exceptional engineering leaders like you to build the teams and platforms that will accelerate the next wave of artificial intelligence.

Widely considered to be one of the technology world’s most desirable employers,

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 208,000 USD - 333,500 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until October 5, 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.

How we rate this

Engineering Manager – AI Platform & SRE at NVIDIA rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

AI AgentsAI AutomationSreDistributed SystemsEngineering ManagementAI PlatformsAutomationKubernetes

Questions you could be asked

  1. How do you decide when an AI agent can act on its own versus asking for approval first?
  2. Tell me about a workflow you automated with AI tools, end to end.
  3. Tell me about a project where sre was part of your work. What did you do?
  4. Tell me about a project where distributed systems was part of your work. What did you do?
  5. Tell me about a project where engineering management was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: AI Agents, AI Automation, Sre, Distributed Systems, and Engineering Management. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
  • Show where AI is part of your daily process, not a one-off project — this role expects it to be a running habit.

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