Senior Platform Software Engineer (CI/CD)

As a Senior Platform Engineer, you will design, build, and evolve the continuous delivery pipelines and Kubernetes-based infrastructure that power our microservices. You will be a domain expert who strengthens the deployment lifecycle, with a focus on ArgoCD, GitOps workflows, and Kubernetes orchestration.

Your primary responsibilities will include:

• Designing, implementing, and maintaining scalable GitOps workflows with Argo CD and Kubernetes that span the entire software development lifecycle, from commit to production.
• Designing and implementing GitHub Actions to orchestrate complex CI workflows, including writing custom actions and managing reusable workflows that support a diverse set of languages and frameworks.
• Partnering with product engineering and developer productivity teams to ensure seamless integration of Kubernetes and CI/CD tooling, acting as a bridge to translate developer friction points into infrastructure improvements.
• Building reusable automation tools and templates (in Go or Python) to abstract away the complexities of Helm and Kustomize, enabling development teams to self-serve their infrastructure needs.
• Keeping the deployment platform aligned with evolving industry standards to reduce operational toil and fragmentation.

To succeed in this role, you will need:

• A Bachelor's or Master's degree in Computer Science, Software Engineering, or related field (or equivalent practical experience).
• 4+ years of software development or infrastructure experience, with a specific focus on Platform Engineering, Kubernetes.
• Familiarity in Kubernetes cluster management and orchestration, with specific hands-on expertise in ArgoCD and GitOps principles.
• Strong programming skills in Golang and Python; experience building internal developer tooling or treating infrastructure as software.
• Knowledge of microservices architecture and cloud-native technologies.
• Strong expertise with CI/CD tools (GitHub Actions, Jenkins) and observability hooks (DataDog) within the deployment lifecycle.
• Demonstrated experience utilizing AI productivity tools (e.g., Cursor, Claude Code) to accelerate SDLC workflows, with proficiency in prompt engineering to optimize code generation, debugging, and documentation tasks.
• Experience with AWS managed services and cloud infrastructure.
• Strong communication skills and the ability to work effectively in a geographically distributed team environment.