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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Cloud DevOps Engineer - **Company:** Auto Club - **Location:** Costa Mesa, CA, United States - **Experience:** Expert - **Salary:** $132,600.0 - $176,900.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Amazon Elastic Compute Cloud, Amazon S3, ARM Architecture, Bash Shell, BigQuery, Cloud Computing, Cyber Security, Computer Programming, Continuous Integration, Data Security, DevOps, Github, Monitoring of Systems, Identity and Access Management, Industry Standard Architecture, Python (Programming Language), Machine Learning, Routing, Tensorflow, Azure Machine Learning, SQL Databases, TCP/IP, Data Logging, Google Cloud, Cloud Platform System, Pytorch, Delivery Pipeline, Snowflake, Software Security, Multi-Cloud, Infrastructure as Code (IaC), Cloudformation, AI Platforms, Kubernetes, Infrastructure Automation Frameworks, Machine Learning Operations, Functional Programming, Cloudwatch, Terraform, AWS EKS, Docker, Amazon Redshift - **Published:** September 25, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=e200e28931966534 ## About the Role * Deep, production-level expertise in either AWS or GCP, with working knowledge of or high adaptability to the other. You are likely to interact with the following core services: * AWS: EKS, S3, IAM, EC2, ECR, SageMaker AI, CloudWatch, Redshift, Lambda. * GCP: GKE, GCS, Cloud IAM, Artifact Registry, Vertex AI, Cloud Logging/Monitoring, BigQuery, Cloud Functions. * Advanced Docker containerization skills, including multi-stage builds and image optimization for heavy ML runtimes (PyTorch/TensorFlow). * Experience with building deployment pipelines using GitHub Actions for CI/CD. * Experience with IaC tools (CloudFormation/Terraform). * Solid understanding of cloud and container networking, routing, and protocols such as TCP/IP, TLS, HTTP/2, and data security best practices such as least privilege access management. * Strong scripting and programming proficiency in Python, Bash, SQL. * Familiarity with configuring Kubernetes (EKS or GKE) for ML workloads. * Experience supporting enterprise data/ML platforms and a willingness to learn and evaluate new vendor capabilities, such as Snowflake Cortex AI and Snowflake ML. * Interest and willingness to research, evaluate, and operationalize emerging AI/ML and cloud technologies. * Cloud Certification in DevOps in AWS or Google Cloud is a plus. ## Description * Multi-Cloud AI/ML Infrastructure: Design, provision, and maintain resilient, scalable multi-cloud infrastructure across AWS and GCP tailored for AI/ML workloads. * Infrastructure as Code (IaC): Automate end-to-end cloud infrastructure and environment provisioning using Terraform and AWS CloudFormation. * End-to-End MLOps Pipelines: Partner with data scientists to design and implement robust CI/CD/CT pipelines for automated model training, testing, validation, artifact packaging, deployment, monitoring and observability. * AI Platform Enablement: Enable and support modern data science platforms (e.g. Amazon SageMaker Unified Studio) and emerging platforms (Snowflake Cortex AI, and Snowflake ML). * Kubernetes Configuration & Management: Deploy and manage production-grade EKS or GKE clusters, optimizing node pools, autoscaling, and compute/GPU resources for ML training and real-time inference. * Cross-Functional Collaboration: Partner with Information Security, Application Security, Data Center Services, and Cloud Infrastructure Services teams to enforce security, governance, and architectural best practices. * Reference Architecture & Best Practices: Partner closely with data scientists to architect and deploy flagship AI/ML products, establishing reusable blueprints, golden paths, and best practice patterns for enterprise-wide adoption. ## Related Videos - [Shipping Faster with Less: Render on Cloud Hosting, AI Workloads, and the Future of DevOps](https://www.wearedevelopers.com/videos/1894-shipping-faster-with-less-render-on-cloud-hosting-ai-workloads-and-the-future-of-devops) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [An Applied Introduction to eBPF with Go](https://www.wearedevelopers.com/videos/1075-an-applied-introduction-to-ebpf-with-go) - [Innovating Developer Tools with AI: Insights from GitHub Next](https://www.wearedevelopers.com/videos/1268-innovating-developer-tools-with-ai-insights-from-github-next) - [DevOps Maturity Check – a way to balance autonomy and alignment](https://www.wearedevelopers.com/videos/58-devops-maturity-check-a-way-to-balance-autonomy-and-alignment) - [Turning Container security up to 11 with Capabilities](https://www.wearedevelopers.com/videos/718-turning-container-security-up-to-11-with-capabilities) ## Related Articles - [7 Cloud Computing Trends Coming in 2025 for Developers](https://www.wearedevelopers.com/magazine/412-7-cloud-computing-trends-coming-in-2025-for-developers) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Best US AI Conferences for CTOs in 2026: Build vs. Buy, Vendor Evaluation, and Peer Intelligence](https://www.wearedevelopers.com/magazine/736-best-us-ai-conferences-for-ctos-in-2026-build-vs-buy-vendor-evaluation-and-peer-intelligence) - [Got AI ideas but no money? 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