This role sits at the intersection of software development and platform engineering, bringing a developer-first mindset to the platform team. You will design and build APIs, automation, and developer portal integrations that enable self-service capabilities and enhance the developer experience for engineering teams running workloads on GKE.
Working closely with application teams, you will help drive platform adoption by delivering scalable, reliable, and intuitive platform capabilities. This role provides an excellent opportunity for a hands-on backend engineer to grow into platform engineering, gaining expertise in GitOps, Kubernetes, service mesh, custom controllers (Go), multi-cluster operations, and production-grade platform development. You will receive mentorship and hands-on support from experienced platform engineers while progressively taking ownership of increasingly complex infrastructure and platform initiatives.
WHAT YOU WILL DO
Design and build backend APIs (REST / OpenAPI) to provision and manage GKE namespaces and clusters - with Swagger-testable contracts, secured via OAuth2 / JWT.
Develop platform automation: custom Kubernetes controllers and operators in Go, and/or backend microservices in Java / Spring Boot (or Node.js), to automate, environment lifecycle, and platform workflows on GKE.
Integrate APIs with our internal developer portal (Red Hat Developer Hub / Backstage): software templates, scaffolder actions, and backend plugins so developers can self-serve namespaces and applications.
Publish and secure APIs through an API gateway (e.g. Apigee) with SSO / OAuth2 / JWT token validation and integrate with our platform API/asset layer.
Onboard and support application teams: help them bring their applications and microservices onto the GKE platform - deployment manifests, Helm charts, CI/CD, observability, service mesh, and connectivity, and act as their trusted partner during migration.
Act as the voice of the developer: use your own hands-on development background to identify developer pain points and shape the platform's paved road so onboarding is genuinely frictionless.
Build and maintain Kubernetes deployment artifacts (Deployments, ReplicaSets, Services, ConfigMaps, Secrets, Ingress/HTTPRoute) and Helm charts for platform and application workloads.
Contribute to CI/CD pipelines (GitHub Actions), container image build/publish, and artifact management for repeatable releases.
Instrument services and build dashboards/alerts in Dynatrace; help app teams onboard to observability.
Work within a service-mesh environment (Cloud Service Mesh / Istio) - secure service-to-service communication (mTLS), traffic management, and resilient inter-service calls.
Participate in the platform on-call rotation - production support, incident response, root-cause analysis, and follow-up remediation.
Contribute to our agentic AI initiative - helping expose platform APIs as MCP servers and integrate them with Gemini Enterprise so developers can onboard services, wire observability, and provision resources through natural-language, AI-assisted workflows.
Collaborate with platform, security, and application teams; write clear documentation; and mentor where appropriate.
Overall Experience: 8–10 years
Relevant Experience: 4–6 years (backend development, APIs, Kubernetes, GitOps , AWS or GCP)
Core Languages: Java / Spring Boot, or Node.js, or Go (Golang)
REQUIRED SKILLS & EXPERIENCE
Hands-on development background: Strong experience as a working software developer - in Java / Spring Boot, Node.js, or Go - so you understand developer workflows and pain points first-hand.
Backend & microservices: Building production microservices and secure REST APIs; Spring Boot / Spring Cloud (or equivalent in Node.js / Go).
API & integration: OpenAPI/Swagger, API integration between microservices and backend systems, API gateways, and authentication with OAuth2, JWT tokens, and SSO.
Kubernetes: Authoring deployment manifests (Deployments, ReplicaSets, Services, ConfigMaps, Secrets) and deploying microservices to managed clusters (GKE/EKS); Docker, Helm.
Automation mindset: Experience automating platform or infrastructure workflows through code - custom controllers/operators (Go) or backend services (Java/Node.js).
GitOps & CI/CD: Argo CD (GitOps) for application delivery; CI/CD pipelines (Jenkins / GitHub Actions), container image build/push, artifact repositories.
Developer enablement: Experience onboarding or supporting application teams - helping them deploy, troubleshoot, and operate their services on a shared platform.
Observability & support: Dynatrace (or similar) - dashboards, log monitoring, instrumentation; production support and on-call incident handling.
Cloud: Working knowledge of a major cloud (GCP and/or AWS); IAM, service accounts, and Workload Identity concepts.
Ways of working: Agile delivery, ownership from design to production support, collaboration, and clear communication.
NICE TO HAVE / WILLINGNESS TO LEARN
Go (Golang) for custom controllers: Experience with or strong interest in learning - Go and Kubebuilder / controller-runtime for building custom Kubernetes controllers and operators.
TypeScript / Node.js: Understanding of TypeScript and Node.js for building Red Hat Developer Hub (Backstage) plugins and scaffolder actions or strong willingness to ramp quickly.
Experience with Red Hat Developer Hub / Backstage, or other internal developer portals / software templates.
Service mesh (Cloud Service Mesh / Istio): mTLS, traffic management, multi-cluster service discovery.
GKE Fleet / Connect Gateway, Workload Identity, GKE networking (Gateway API, internal load balancing, DNS).
Agentic AI & MCP: Interest in or experience with building agentic AI capabilities on the platform: exposing GKE platform APIs as MCP (Model Context Protocol) servers and integrating them with Gemini Enterprise Agent Platform to enable AI-assisted developer self-service.
Cloud certifications (e.g. Google Cloud / AWS Solutions Architect or Developer Associate).
AI-assisted development tooling (GitHub Copilot, Cursor) and prompt-engineering practices.
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