What you ll do
Infrastructure Architecture & Automation
- Design and build cloud infrastructure from scratch; modernize existing enterprise environments.
- Implement IaC using Terraform / Pulumi / CloudFormation.
- Architect VPCs, networking, load balancing, autoscaling, high availability, and secure connectivity.
- Implement scalable, cost-efficient cloud environments following best practices.
Cloud Expertise
- Deep hands-on expertise in one cloud provider (AWS / GCP / Azure).
- Strong understanding of compute, networking, storage, security (IAM/KMS), managed databases, and messaging services.
- Experience designing multi-AZ/region architectures and working with cloud-native security.
Kubernetes & Cloud-native Platform Engineering
- Hands-on experience with Kubernetes (EKS/GKE/AKS, Kops, Rancher, Openshift) in production.
- GitOps workflows using ArgoCD / FluxCD.
- Knowledge of autoscaling (HPA/VPA/Karpenter), Helm, service mesh (Istio/Linkerd), and cluster security (RBAC, PSP/PSS, network policies).
- Container security, image scanning, and runtime protection.
Observability, Monitoring & SRE Practices
Implement SRE frameworks: SLIs, SLOs, error budgets, incident response, postmortems. Capacity planning, performance tuning, and system reliability improvements. CI/CD, DevOps & GitOps
- Design end-to-end CI/CD pipelines using GitHub Actions, GitLab CI, Jenkins, Tekton, etc.
- Implement GitOps-based environment promotion and automated deployment workflows.
- Manage artifacts (JFrog, Nexus), image registries, and release versioning.
- Apply DevSecOps: SAST/DAST, dependency scanning, SBOM, policy-as-code (OPA/Kyverno).
Security & Compliance (Nice to have)
- Cloud and Kubernetes security (IAM, secrets management, Vault, SOPS, KMS).
- Network policies, mTLS, service mesh security.
- Exposure to enterprise compliance (SOC2, ISO27001, GDPR).
- Experience with CSPM, policy enforcement, and vulnerability management
Architecture Modernization & Microservices (Nice to have)
- Experience modernizing legacy workloads and supporting microservices architectures.
- Knowledge of service mesh, API gateways, distributed systems, and hybrid environments.
- Migration of monolith microservices (or VM container/k8s).
MLOps & Data Platform Support (Nice to have)
- Exposure to MLOps tools: Kubeflow, MLflow, SageMaker.
- Deploying GPU workloads and model-serving pipelines.
- Basic understanding of data pipelines, feature stores, metadata tracking.
To be successful in this role, you should have
Qualifications - BE / BTech in Computer Science, Data Engineering, or related fields from premier institutes (IITs, NITs, BITS, etc.)
- 8 to 12 years of experience in DevOps / Cloud / Platform Engineering
- Proven experience designing and operating large-scale production systems
Core Skills
- Cloud platforms, Kubernetes, CI/CD
- Observability, security, and DevOps/GitOps practices
- Legacy modernization, microservices, and MLOps support
