AI Cloud Senior DevOps Engineer

13 days ago

Remote, United States or San Jose, CA, USASenior

Responsibilities

Design, implement, and maintain end-to-end CI/CD and MLOps pipelines for applications and machine learning models.
Build, optimize, and scale Kubernetes- and Docker-based cloud-native infrastructure, including GPU clusters for AI workloads and model inferencing.
Own high-availability architecture, disaster recovery, self-healing, capacity planning, and production performance tuning.
Automate reproducible infrastructure provisioning across cloud environments using Terraform, Ansible, Helm, and infrastructure-as-code practices.
Develop monitoring, logging, and alerting systems for infrastructure, applications, and AI model metrics.
Partner with R&D, Data Science, Security, and Business teams on Internal Developer Platforms and platform engineering initiatives.
Establish security, governance, release management, secrets management, Zero Trust access controls, and compliance practices.
Lead major incident response, troubleshooting, root cause analysis, and preventative remediation.
Mentor engineers or manage DevOps teams when needed.

Bachelor's degree or higher in Computer Science, Engineering, or a related technical field.
At least 5 years of hands-on experience in DevOps, Site Reliability Engineering, or cloud infrastructure roles.
Expert knowledge of Linux operating systems and networking concepts including TCP/IP, DNS, HTTP, load balancing, and VPCs.
Deep production-level expertise with Docker and Kubernetes, including cluster management and orchestration principles.
Experience designing and managing infrastructure on AWS, GCP, Azure, Alibaba Cloud, or other major public or hybrid cloud platforms.
Strong programming and scripting ability in at least one major language such as Go, Python, or Shell.
Practical understanding of CI/CD, infrastructure as code, observability, and Site Reliability Engineering principles.
Preferred experience with MLOps, vLLM, TGI, Triton Inference Server, GPU clusters, and AI/ML workloads.
Preferred experience with large-scale distributed systems, high-concurrency environments, Internal Developer Platforms, Zero Trust architecture, DevSecOps, SOC2, and ISO27001.
Preferred technical leadership, mentoring, or DevOps team management experience.

201-500 employees