Key Responsibilities

- Design, implement, and maintain highly available, scalable, and reliable infrastructure.

- Manage, monitor, and troubleshoot Kubernetes clusters, workloads, deployments, and cluster-level issues.

- Design and maintain CI/CD pipelines for reliable application build, deployment, release, and rollback.

- Implement deployment strategies including Canary, Blue-Green, and Rolling Deployments.

- Troubleshoot pipeline failures, deployment issues, configuration problems, application failures, and service communication issues.

- Develop automation using Python, Bash, Go, or similar scripting languages to reduce operational toil.

- Monitor system availability, performance, capacity, and reliability using modern observability and monitoring tools.

- Troubleshoot issues across application, infrastructure, Kubernetes, cloud, and networking layers.

- Participate in incident management, root-cause analysis (RCA), and preventive/corrective actions.

- Collaborate with Development, DevOps, Cloud, Platform, and Security teams to improve reliability and operational processes.

Mandatory Skills

- Kubernetes (K8s) - strong hands-on administration and troubleshooting.

- Cloud: AWS, Azure, or GCP.

- CI/CD: Jenkins, GitLab CI/CD, GitHub Actions, Azure DevOps, Argo CD, or similar.

- Scripting/Programming: Python, Bash, or Go.

- Networking: TCP/IP, DNS, HTTP/HTTPS, routing, subnets/CIDR, load balancing, firewalls/security groups, and service connectivity.

- Containerization: Docker and Kubernetes.

- Robust production troubleshooting and incident management experience.

- Strong experience in automation and operational engineering.

Kubernetes Expertise

Hands-on Experience With





- Kubernetes architecture and control-plane components

- API Server, Scheduler, Controller Manager, etcd, and kubelet

- Pods, Deployments, StatefulSets, DaemonSets, and Jobs

- Services, Ingress, ConfigMaps, and Secrets

- Resource requests/limits and workload scheduling

- Cluster networking and service discovery

- Troubleshooting CrashLoopBackOff, ImagePullBackOff, scheduling, rollout, node health, connectivity, and resource issues

Cloud & Infrastructure

- Hands-on experience with AWS / Azure / GCP infrastructure and native services.

- Knowledge of compute, storage, networking, IAM, load balancing, security, monitoring, and logging.

- Experience with Infrastructure as Code (IaC) using Terraform, CloudFormation, ARM/Bicep, or similar tools.

Observability & Reliability

- Experience with metrics, logs, and traces.

- Exposure to Prometheus, Grafana, ELK/Elastic, Splunk, Datadog, New Relic, or cloud-native monitoring tools.

- Understanding of SLI, SLO, SLA, alerting, incident response, and RCA.

Preferred Qualifications

- Experience supporting production-grade distributed systems and microservices.

- Experience in 24x7 production support / SRE environments.

- Strong Linux/Unix fundamentals.

- Experience with Git and Git-based workflows.

- Experience with Terraform/IaC and configuration management.

- Strong analytical, troubleshooting, communication, and problem-solving skills.

Experience

3+ years of experience in SRE, DevOps, Cloud Infrastructure, Platform Engineering, or related roles.

Mandatory Core Skills

Kubernetes + AWS/Azure/GCP + CI/CD + Python/Bash/Go + Networking + Containerization + Automation + Production Troubleshooting

📌 Site Reliability Engineer (SRE) (Bengaluru)
🏢 Synectics Apac
📍 Bengaluru