Nvidia Engineering Manager - AI DevOps 

United States, Texas 

399498192

What you'll be doing:

• Supervise a team of DevOps engineers with expertise in AI inference infrastructure, test automation (SDET), and Infrastructure as Code (IaC)

• Architect and implement scalable test automation strategies for AI inference workloads, including performance benchmarking and automated quality gates

• Lead the maintenance of our GitHub First public CI infrastructure, focusing on single/multi-GPU testing, Kubernetes multi-node GPU testing, and CSP validation

• Drive Infrastructure as Code efforts by employing Terraform, Ansible, and Kubernetes to support scaling across multiple clouds and lead GPU clusters effectively.

• Attain operational proficiency encompassing 24x7 on-call rotations, SRE methodologies, automated monitoring, and self-repairing systems to guarantee uptime exceeding 99.9%

• Lead release coordination, cost optimization, and management of multi-cloud deployments

What we need to see:

• Bachelor's/Master's degree in Computer Science, Engineering, or equivalent experience

• 4+ years leading DevOps/SRE organizations with direct SDET leadership experience

• 8+ years hands-on experience in software development, test automation, or infrastructure engineering with AI/ML or GPU-intensive workloads

• Proficiency in Infrastructure as Code (IaC) platforms: Terraform, Ansible, or CloudFormation with exposure to multiple cloud environments (AWS, GCP, Azure, OCI)

• Strong technical leadership in test automation frameworks, CI/CD pipeline development, and quality engineering practices

• Familiarity with containerization and orchestration tools such as Docker and Kubernetes for leading AI/ML workloads and GPU resources

• Proven success building and scaling teams in fast-paced, high-growth environments

• Effective interpersonal skills to collaborate with remote teams and build agreement

• Proficiency in Python, Rust, or related programming languages along with the capability to engage in architecture conversations

• Demonstrated history of operational proficiency encompassing 24x7 on-call oversight, SRE methodologies, and robust high-availability infrastructures

Ways to stand out from the crowd:

• Experience with CI/CD (specifically GitHub Actions), releasing Open-source AI software

• Proficient in Deep AI/ML infrastructure with expertise in NVIDIA technologies such as CUDA, TensorRT, Dynamo and Triton Inference Server, including coordinating GPU cluster operations and GPU workload performance benchmarking

• Background in DevOps, system software testing, and previous experience leading teams on inference engines, model serving platforms, or AI acceleration frameworks

• Track record with monitoring tools (Prometheus, Grafana), security scanning, static/dynamic analysis tools, and license compliance automation for critical AI inferencing frameworks.