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We are seeking a Senior DevOps Engineer to design, deploy, and operate the next generation of Inflection AI’s cloud and AI infrastructure. This role sits at the intersection of AI research and production systems, owning the reliability, scalability, and performance of GPU-enabled platforms that power large-scale LLM training and inference. You will work across Azure and AWS to build highly automated, observable, and resilient infrastructure supporting low-latency AI applications in production.
Job Responsibility:
Architect, deploy, and operate large-scale LLM inference servers and AI applications with a focus on low latency, high availability, and production reliability
Design, provision, and maintain complex cloud architectures across Azure and AWS, including storage, compute, networking, databases, and native LLM services
Manage GPU-enabled Kubernetes clusters and Slurm-based HPC environments, optimizing resource allocation for AI training and inference workloads
Deploy and operate core Kubernetes infrastructure components and operators (GPU operators, ingress controllers, service meshes, CNIs, CSIs, and storage drivers)
Build scalable infrastructure-as-code and deployment workflows using Terraform, Helm, Kustomize, ArgoCD, and GitOps best practices
Design and maintain centralized observability systems using Prometheus, Grafana, Clickhouse, and cloud-native monitoring tools
Participate in on-call rotations, lead incident response, perform post-mortems, and continuously improve system reliability and SLAs.
Requirements:
5+ years of hands-on experience in DevOps, Site Reliability Engineering, or ML Infrastructure supporting high-scale, production systems
Deep expertise in Azure and AWS, including storage, compute, networking, databases, and cloud-native monitoring services
Strong Kubernetes administration experience, including GPU scheduling, operator deployment, and management of core infrastructure components
experience with Slurm is highly desirable
Proven experience deploying, scaling, and operating Large Language Models (LLMs) and inference engines such as vLLM, TGI, or Triton
Strong experience with modern DevOps tooling: Terraform, Helm, Kustomize, ArgoCD, GitHub Actions or GitLab CI, Prometheus, Grafana, and Clickhouse
Advanced scripting and automation skills in Python and Bash, with the ability to debug complex distributed systems and optimize performance at scale
Demonstrated ability to troubleshoot LLM servers, Kubernetes workloads, GPU utilization, and cloud infrastructure bottlenecks
Have a bachelor’s degree or equivalent in a related field to the offered position requirements.
What we offer:
Diverse medical, dental and vision options
401k matching program
Unlimited paid time off
Parental leave and flexibility for all parents and caregivers
Support of country-specific visa needs for international employees living in the Bay Area