About this role
Join the Global Dev Tools team within the Enterprise Platform Engineering and Operations (EPEO) organization to build and operate the cloud-native platform that powers Ford's Software Development Lifecycle (SDLC). As a Senior DevOps Engineer, you will play a hands-on, technical role in enabling Product Development Office (PDO) teams. You will design, build, and operate the infrastructure, CI/CD pipelines, and automation that let engineering teams ship reliably and often.
Your work will center around Ford's core tech stack, featuring Google Cloud Platform (GCP) and Azure for cloud infrastructure, and GitHub Enterprise with GitHub Actions and Jenkins for CI/CD. Infrastructure is fully codified with Terraform, with GitHub Actions Runner Controller (ARC) self-hosted runners deployed on Kubernetes (GKE) to power scalable, on-demand CI/CD. You'll support Actions workflows that build and deploy Java (Spring Boot), Go, and Python applications, orchestrate AI agents to automate operational toil, lead technical evaluations of emerging AI developer and infrastructure tools, and ensure all platform systems meet Ford's stringent performance, security, and scalability benchmarks.
- Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a closely related technical field.
- 8 years of Hands-on DevOps/Platform Engineering experience
- Strong programming ability in a real language — Python and/or Go preferred — with a track record of shipping production code
- Proficiency authoring YAML for CI/CD pipelines, Kubernetes manifests, and configuration-as-code
- Strong Git and GitHub workflow experience — branching strategies, pull requests, and repository management at scale
- Solid scripting ability in Bash/Shell/python for automation and operational tooling
- Deep, hands-on GCP experience (GKE, and ideally Cloud Run, Compute Engine, Cloud Functions, networking, IAM) at production scale
- Strong Infrastructure-as-Code experience with Terraform, provisioning GCP resources broadly — compute, storage, networking, and GKE clusters
- Hands-on CI/CD pipeline experience with GitHub Actions and/or Jenkins
- Production experience containerizing applications (Docker or Podman) and operating them at scale on Kubernetes, including diagnosing and resolving cluster-level issues
- Experience with GitOps tooling (e.g., Config Sync, ArgoCD, or Flux) for declarative, version-controlled infrastructure and workload deployment
- Experience integrating and configuring SonarQube (or equivalent) within CI/CD pipelines for code quality and security scanning
- API design and integration experience, including RESTful services and API gateway management (Apigee, OAuth2, JWT)
- Hands-on experience with GCP BigQuery and Data Studio/Looker Studio for building observability and reporting dashboards
- Observability chops — metrics, logs, tracing — and the judgment to find the needle, not just collect haystacks
- Knowledge and hands-on experience designing, developing, and implementing AI/ML products, along with fluency in AI-assisted development tools (GitHub Copilot, JetBrains AI Assistant, Cursor AI, QODO, or open-source alternatives) and agent workflows, with clear judgment on where they help and where they don't
- Working knowledge of SLOs, incident response, and security-by-default pipeline design
- A customer-focused mindset — able to balance developer experience with security and compliance requirements
- Demonstrated ability to identify process gaps and drive continuous improvement initiatives
- Bonus: experience running LLM/agentic systems, GPUs, or model-serving infrastructure in production