Multi-Cloud DevOps Engineer (AWS + Azure + Kubernetes) — Capgemini · Bangalore

About the role

Multi-cloud DevOps engineer for Capgemini India — design and operate workloads across AWS, Azure and GCP with Kubernetes, GitOps and service-mesh patterns. 4-12 years, hybrid Bangalore preferred, other India metros open.

About this role and the team at Capgemini. Multi-cloud DevOps engineer for Capgemini India — design and operate workloads across AWS, Azure and GCP with Kubernetes, GitOps and service-mesh patterns. 4-12 years, hybrid Bangalore preferred, other India metros open. This listing on cloudsoftsol.com is curated for engineers in India who are actively interviewing for senior cloud and DevOps roles. If you are seeking a multi-year career platform rather than a stop-gap, this listing rewards depth — read the responsibilities and requirements below carefully and tailor your application to the specifics. We do not charge candidates a fee for placement assistance; companies sponsor our involvement.

Responsibilities

Architect and operate workloads across AWS, Azure and GCP for Capgemini's multi-cloud client portfolio — landing zones, hub-and-spoke networks, identity federation, and unified observability. Author cloud-agnostic Terraform modules wherever possible, with provider-specific specialisations for EKS, AKS and GKE; maintain them in the Capgemini internal registry with semantic versioning and security-scan gates. Operate Kubernetes clusters across all three clouds: cluster lifecycle management, Helm-packaged platform add-ons, IRSA / Workload Identity / GKE Workload Identity for least-privilege workload IAM, and a service-mesh layer (Istio or Linkerd) where the client demands mTLS or fine-grained traffic shaping. Implement GitOps delivery via ArgoCD or FluxCD with environment promotion through git PRs, ApplicationSets for fleet-scale deployments, and progressive-delivery patterns (canary, blue-green, traffic shifting via the mesh). Design and run CI pipelines in whichever toolchain the client uses — Jenkins, GitHub Actions, Azure DevOps Pipelines or GitLab CI — with reusable workflow libraries and image-signing via cosign. Lead DevSecOps adoption: SAST / DAST / IaC scanning in CI, secrets management (HashiCorp Vault, AWS Secrets Manager, Azure Key Vault), and centralised SIEM ingestion. Drive FinOps practices: cost allocation, budget alerts, anomaly detection, Reserved Instance / Savings Plan modelling, Azure Hybrid Benefit and GCP CUDs. Produce monthly client-facing FinOps reports with realised savings. Run blameless post-incident reviews, codify learnings into runbooks, and contribute back to Capgemini's internal multi-cloud playbook.

Requirements & qualifications

4-12 years of DevOps / Platform Engineering experience with hands-on production exposure to at least two of AWS, Azure and GCP. Deep Kubernetes — at least 2 years of EKS, AKS or GKE in production at meaningful scale (50+ nodes, multiple namespaces and tenants). Strong Terraform; comfortable across the three cloud providers' Terraform modules and provider quirks. Working knowledge of at least one service mesh (Istio or Linkerd) and one GitOps tool (ArgoCD or Flux). Solid scripting in Python or Go, plus shell. DevSecOps and FinOps awareness; comfortable presenting cost and security trade-offs to client architects. Cloud certifications across two providers preferred (e.g., AWS Professional + Azure Solutions Architect Expert + CKA / CKAD). Excellent communication — you will be client-facing.

Why this role in 2026

Multi-cloud is where Capgemini's deepest accounts live and where the most interesting platform-engineering problems sit. Engineers with proven experience across two or more hyperscalers are scarce in the Indian market and command meaningfully higher offers — both inside Capgemini's grade ladder and outside.

Application tips

Use the global Capgemini careers portal (link below) and filter by India + DevOps / Cloud roles. Mention specifically which two or three clouds you have run in production; recruiters route multi-cloud profiles to a different intake desk than single-cloud applications.

Interview preparation

Five-round loop: HR, technical screen on Kubernetes + Terraform, hands-on coding (cross-cloud Terraform module or scripted cost-anomaly detector), multi-cloud system design (e.g., active-active workload across AWS + Azure with global ingress and shared identity), and a client-facing communication round. Brush up on GitOps progressive delivery and FinOps fundamentals.

Career growth

Path: Senior Cloud Engineer → Lead → Cloud Architect → Principal Architect / Practice Lead. Multi-cloud profiles also feed into Capgemini's Cloud Strategy and Cloud Advisory consulting tracks for engineers who want a more advisory-shaped career.