Senior DevOps Engineer, AIOps

NVIDIA is powering the world’s most advanced AI factories, where resilient infrastructure is essential to keep accelerated computing environments running at scale. The Agentic AIOps team is building a mission-critical observability and prediction platform - delivered as both a high-scale SaaS solution and a robust on-premises deployment for NVIDIA’s largest enterprise customers.

As a Senior DevOps Engineer, you’ll help turn agentic AI capabilities for diagnosing and troubleshooting network and GPU infrastructure into secure, scalable, production-ready services. This role stands out through its end-to-end ownership across cloud and customer-managed environments, close partnership with software and AI engineers, and direct influence on the reliability of NVIDIA’s AI infrastructure.

What You'll Be Doing:

• Own the DevOps, infrastructure, security, release, and reliability lifecycle - from development environments and CI/CD through deployment, production readiness, and sustained operations.
• Build and operate Kubernetes environments and Helm-based deployments for a Python, FastAPI, Node.js, and React microservices platform across SaaS and on-premises footprints.
• Engineer GitLab CI/CD pipelines with automated testing, container builds, vulnerability scanning, and versioned image and Helm chart publication through JFrog Artifactory.
• Automate infrastructure provisioning, configuration, upgrades, and routine operational workflows to accelerate delivery and improve engineering productivity.
• Operate PostgreSQL, Temporal workflow services, and S3-compatible object storage with disciplined capacity planning, backups, recovery testing, and safe migrations.
• Strengthen release reliability through deployment validation, reduced-downtime strategies, persistent-state protection, and recovery plans for active workflows.
• Deliver actionable observability and security using OpenTelemetry, Datadog/Grafana, Langfuse, secrets management, identity integration, TLS, Kubernetes RBAC, network policies, and container hardening.
• Partner with software and AI engineers to troubleshoot distributed systems, investigate incidents, define reliability targets, and improve platform performance, resource efficiency, and customer outcomes.

What We Need to See:

• Bachelor’s degree in Computer Science, Software Engineering, or a related field, or equivalent experience.
• 5+ years of experience in DevOps, site reliability engineering, or platform engineering supporting distributed applications and microservices.
• Strong hands-on experience with Kubernetes, Docker, and Helm, including networking, storage, workload scheduling, scaling, and troubleshooting.
• Strong Linux administration skills and proficiency in Python and Bash for automation, plus experience with infrastructure as code and configuration tooling such as Terraform and Ansible.