Location: INDIA (Remote)

Employment Type: Full time / Contract

Experience Level: 7+ Years

About the Role

We are seeking a hands-on engineer with deep expertise in chaos engineering, performance/load testing with K6, and AWS compute optimization across EKS (Kubernetes) and ECS. This role is central to improving the resilience, scalability, and cost-efficiency of our production infrastructure by proactively identifying failure modes, validating system behavior under load, and tuning compute resources for performance and cost.

Key Responsibilities

- Design, implement, and run chaos engineering experiments (e.g., pod/node failure, network latency injection, resource starvation, AZ/region failure simulation) using tools such as Chaos Mesh, LitmusChaos, Gremlin, or AWS Fault Injection Simulator (FIS).
- Build and maintain K6 performance/load testing scripts to validate throughput, latency, and stability of services under varying load conditions; integrate K6 into CI/CD pipelines for continuous performance validation.
- Analyze test and chaos experiment results to identify bottlenecks, single points of failure, and degradation patterns; produce actionable remediation recommendations.
- Optimize AWS EKS cluster configurations — node groups, Karpenter/Cluster Autoscaler, pod resource requests/limits, HPA/VPA tuning, and workload right-sizing.
- Optimize AWS ECS (Fargate and EC2 launch types) task definitions, service scaling policies, and cluster capacity providers for cost and performance efficiency.
- Drive compute cost optimization initiatives — Spot/Reserved/Savings Plans strategy, right-sizing, bin-packing, and resource utilization analysis across EKS/ECS workloads.
- Collaborate with SRE, DevOps, and application teams to define resilience SLOs/SLIs and embed chaos/performance testing into the software delivery lifecycle.
- Build observability and reporting around chaos experiments and load tests (dashboards, alerts, post-experiment reports)



using tools such as CloudWatch, Prometheus/Grafana, or Datadog.
- Document runbooks, failure scenarios, and lessons learned; contribute to a culture of resilience engineering and continuous improvement.

Required Skills & Experience
- Proven hands-on experience with chaos engineering practices and tooling (Chaos Mesh, Gremlin, LitmusChaos, AWS FIS, or equivalent).
- Strong practical experience writing and executing K6 test scripts (load, stress, spike, soak testing), including scripting in JavaScript and integrating K6 with CI/CD.
- Deep working knowledge of AWS EKS — cluster architecture, node/pod scaling, autoscaling strategies, networking (VPC CNI, security groups), and workload optimization.
- Deep working knowledge of AWS ECS — Fargate/EC2 launch types, task/service definitions, capacity providers, and auto-scaling configuration.
- Experience with AWS compute cost optimization techniques (Spot instances, Savings Plans, right-sizing, Compute Optimizer).
- Solid understanding of Kubernetes fundamentals (Deployments, Services, HPA/VPA, resource quotas, node affinity/taints).
- Experience with Infrastructure-as-Code (Terraform, CloudFormation, or CDK) for provisioning and managing EKS/ECS environments.
- Familiarity with observability stacks (Prometheus, Grafana, CloudWatch, Datadog, or similar) for monitoring resilience and performance metrics.
- Strong scripting/automation skills (Python, Bash, or Go).
- Excellent troubleshooting skills with the ability to root-cause distributed system failures under load.

Preferred / Nice-to-Have
- AWS Certifications (Solutions Architect, DevOps Engineer, or SysOps Administrator).
- Certified Kubernetes Administrator (CKA) or equivalent.
- Experience with GitOps tools (ArgoCD, Flux) and CI/CD platforms (Jenkins, GitLab CI, GitHub Actions).
- Exposure to service mesh technologies (Istio, App Mesh) for fault injection testing.
- Prior experience running Game Days or resilience/DR exercises in production environments.

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