NVIDIA is building the computing platforms that power the next era of AI, and reliable software delivery is essential to operating them at scale. Join the team building NVIDIA’s AI Ops platform for large-scale AI infrastructure, where telemetry and operational capabilities help customers run complex AI factories. This role combines platform engineering, release ownership, and production operations across cloud, on-premises, Kubernetes, Docker Swarm, and air-gapped environments. The work spans the full path from a developer’s commit to a secure, observable customer deployment, with close partnership across engineering, QA, security, product, and support.
What you’ll be doing:
- Build and evolve CI/CD pipelines and reusable developer-platform workflows that automate build, test, security scanning, publishing, deployment, and promotion across services.
- Own release mechanics end to end, including versioning, artifact and image lifecycle, upgrades, rollbacks, and controlled rollout across environments.
- Deploy and operate the platform across Kubernetes, Docker Swarm, AWS, on-premises infrastructure, and air-gapped customer environments; manage infrastructure as code and declarative GitOps across environments and accounts.
- Integrate security into delivery through vulnerability scanning, secrets management, SBOM generation, and open-source license compliance.
- Strengthen the reliability of containerized and stateful services through high availability, backup and restore, observability, dashboards, alerting, runbooks, and incident response; participate in cloud-service on-call as needed.
- Improve engineering velocity and service maturity through faster builds, caching, reproducible environments, clear deployment standards, operational tooling, and better onboarding in partnership with engineering, QA, security, product, and support.
What we need to see:
- Bachelor’s degree in Computer Science, Computer Engineering, or a related field, or equivalent experience.
- 5+ years of experience in DevOps, SRE, Platform Engineering, or Release Engineering.
- Hands-on experience with AWS and infrastructure automation using tools such as Terraform and Ansible; strong Linux and networking troubleshooting skills.
- Proven experience building and maintaining CI/CD pipelines with GitLab CI/CD, Jenkins, or similar tools, including artifact publishing and release workflows.
- Strong experience with Docker, Kubernetes, Helm, image registries, and container lifecycle management; experience with GitOps tools such as ArgoCD or Flux.
- Practical DevSecOps experience integrating vulnerability scanning, secrets handling, SBOMs, and compliance checks into CI/CD workflows.
- Strong scripting and automation skills in Python, Bash, or similar, and experience with production observability tools such as Prometheus, Grafana, ELK, or similar.
Ways to stand out from the crowd:
- Experience delivering software into on-premises or air-gapped customer environments.
- Experience operating stateful distributed data services such as Kafka, MySQL, or Redis in production.
- Background with GPU, HPC, AI, or other large-scale infrastructure platforms.
- Experience building internal developer platforms that measurably improve engineering velocity and release reliability, or helping a product mature into a customer-facing SaaS offering.
- Kubernetes or AWS certifications, or hands-on use of AI-assisted engineering tools.