Company Profile:
Founded in 1976, CGI is among the largest independent IT and business consulting services firms in the world. With 94,000 consultants and professionals across the globe, CGI delivers an end-to-end portfolio of capabilities, from strategic IT and business consulting to systems integration, managed IT and business process services and intellectual property solutions. CGI works with clients through a local relationship model complemented by a global delivery network that helps clients digitally transform their organizations and accelerate results. CGI Fiscal 2024 reported revenue is CA$14.68 billion and CGI shares are listed on the TSX (GIB.A) and the NYSE (GIB). Learn more at cgi.com.

Position: DevOps Engineer-Kubernetes (4-8 Years)
Experience: 4-8 years
Category: Software Development/ Engineering
Shift: 12:00 PM-10:00 PM
Location: Bangalore/Hyderabad/Pune
Position ID: J0826-1850
Employment Type: Full Time

Education Qualification: Bachelor’s degree in computer science or related field or higher with minimum 4 years of relevant experience.

We are looking for a hands-on Cloud and Kubernetes DevOps Engineer to support the deployment, administration, monitoring, troubleshooting, and maintenance of enterprise cloud and Kubernetes environments.

The candidate must have a strong understanding of cloud-native concepts that can be applied across different cloud providers.

The selected candidate will work closely with senior DevOps engineers, application teams, database teams, networking teams, cloud infrastructure teams, and security teams. The candidate should be able to take ownership of assigned tasks, follow established processes, troubleshoot infrastructure and application-platform issues, document findings, and provide timely status updates.

Your future duties and responsibilities

Administer and support managed Kubernetes environments such as AKS, EKS, and GKE across development, QA, and production environments.

Deploy, configure, troubleshoot, and maintain Kubernetes workloads, including Deployments, StatefulSets, DaemonSets, Services, Ingress resources, ConfigMaps, Secrets, Jobs, and CronJobs.

Troubleshoot pod startup failures, CrashLoopBackOff conditions, OOMKilled events, scheduling failures, resource constraints, readiness failures, storage issues, and application connectivity problems.

Manage Kubernetes worker-node pools, including scaling, upgrades, node replacement, workload migration, taints, tolerations, node selectors, affinity rules, and capacity planning.

Support cloud infrastructure such as virtual networks, VPCs, subnets, security groups, network security rules, route tables, private endpoints, private DNS, load balancers, storage services,



container registries, and key-management services.

Logging and Incident Troubleshooting: Ability to analyze application logs, Kubernetes events, metrics, alerts, and operating-system logs to isolate infrastructure, platform, network, or application issues.

Infrastructure as Code: Working knowledge of Terraform. Exposure to Bicep, ARM templates, CloudFormation, or equivalent tools is beneficial.

CI/CD and Source Control: Experience with Git and platforms such as Azure DevOps, GitHub Actions, Jenkins, GitLab CI/CD, Cloud Build, or CodePipeline.

Scripting: Ability to write and modify Bash scripts. Python or PowerShell knowledge is preferred.

Helm and YAML: Hands-on experience deploying and troubleshooting applications using Helm charts and Kubernetes YAML manifests.

Platform Services: Exposure to PostgreSQL, Redis, Keycloak, APISIX, NGINX, Weaviate, or similar enterprise platform services.

Production Operations: Experience supporting releases, maintenance, patching, upgrades, incidents, backup validation, high availability, and disaster recovery.

Security and Compliance: Basic understanding of vulnerability remediation, secrets management, TLS, encryption, access control, and enterprise compliance processes.

Required qualifications to be successful in this role

Must to have skills-

Hands-on experience with public cloud platforms, Kubernetes, Linux, and DevOps operations.

Public Cloud: Solid hands-on experience with at least one major cloud platform—Azure, AWS, or Google Cloud—and the ability to learn and work across other cloud platforms.

Managed Kubernetes: Hands-on experience with AKS, EKS, or GKE, including cluster administration, upgrades, scaling, node pools, and production support.

Kubernetes Troubleshooting: Strong knowledge of pods, Deployments, StatefulSets, Services, Ingress, ConfigMaps, Secrets, Jobs, CronJobs, probes, resource requests/limits, OOMKilled, CrashLoopBackOff, and Pending pod issues.

Kubernetes Scheduling: Experience with node selectors, affinity, anti-affinity, taints, tolerations, PodDisruptionBudgets, autoscaling, and workload migration.

Containers: Hands-on experience with Docker, Podman, containerd, container images, registries, and container troubleshooting.

Linux Administration: Strong Linux troubleshooting skills covering systemd, journalctl,



processes, permissions, filesystems, CPU, memory, disk, and network issues.

Cloud Networking: Knowledge of VPCs/VNets, subnets, routing, firewalls, security groups, private endpoints, private DNS, load balancers, NAT, VPNs, and hybrid connectivity.

Network Troubleshooting: Ability to use curl, nc, dig, nslookup, traceroute, ss, openssl, and related tools to diagnose DNS, TLS, routing, and port-connectivity issues.

Identity and Access Management: Experience with cloud IAM, Kubernetes RBAC, service accounts, workload identities, managed identities, service principals, roles, and access controls.

Storage: Experience with Kubernetes persistent volumes, storage classes, managed disks, file storage, snapshots, backup, restore, and disaster-recovery validation.

Monitoring and Observability: Experience with Prometheus, Grafana, OpenTelemetry, SigNoz, CloudWatch, Azure Monitor, Google Cloud Operations, or equivalent tools.

Good to have skills-

AI/GenAI Platform Operations: Experience deploying, supporting, monitoring, and troubleshooting AI/GenAI workloads, model endpoints, RAG pipelines, and AI agents on cloud and Kubernetes platforms.

AI Infrastructure and Integration: Familiarity with vector databases, GPU workloads, managed AI services, AI APIs, authentication, observability, performance, scaling, and security.

Together, as owners, let’s turn meaningful insights into action.

Life at CGI is rooted in ownership, teamwork, respect and belonging. Here, you’ll reach your full potential because…

You are invited to be an owner from day 1 as we work together to bring our Dream to life. That’s why we call ourselves CGI Partners rather than employees. We benefit from our collective success and actively shape our company’s strategy and direction.

Your work creates value. You’ll develop innovative solutions and build relationships with teammates and clients while accessing global capabilities to scale your ideas, embrace new opportunities, and benefit from expansive industry and technology expertise.

You’ll shape your career by joining a company built to grow and last. You’ll be supported by leaders who care about your health and well-being and provide you with opportunities to deepen your skills and broaden your horizons.

That same commitment to fairness extends to how we use technology. To support our recruitment team, AI tools may be used to help assess applications though they never replace human judgement. All hiring decisions remain entirely in the hands of our recruitment professionals.

Come join our team—one of the largest IT and business consulting services firms in the world.

📌 DevOps Engineer-Kubernetes (4-8 Years) (India)
🏢 CGI
📍 India