DevOps/ Site Reliability Engineer

6 days ago

Bangalore, India Xebia Full time

We are looking for a highly skilled AWS Engineer with strong Python development and Chaos Engineering expertise to design, build, and validate resilient, scalable, and automated cloud-native environments. The ideal candidate will combine cloud engineering, DevOps, and chaos experimentation to improve reliability, fault tolerance, and operational efficiency of critical systems. Cloud Engineering (AWS): ~6–10 years of experience in Cloud, DevOps, or SRE roles. Strong hands-on expertise in AWS Cloud (certifications preferred: AWS DevOps Engineer / Solutions Architect) Architect, implement, and manage secure, scalable, and cost-efficient AWS infrastructure (EC2, Lambda, EKS, S3, RDS, IAM, CloudFront, etc.). ~ Automate infrastructure provisioning and configuration using Terraform / CloudFormation and AWS SDKs. ~ Manage containerized workloads (Docker, Kubernetes, EKS). Python Development: Build automation scripts, deployment utilities, and infrastructure tooling using Python (Boto3, Flask, FastAPI, etc.) . Advanced Python development skills for automation and tooling (Boto3 a must). Develop custom monitoring/alerting integrations with APIs, SDKs, and third-party observability platforms. Chaos Engineering & Resiliency: Use tools like Gremlin, Litmus, Chaos Mesh, or AWS Fault Injection Simulator . Experience designing and running chaos experiments (Gremlin, AWS FIS, Litmus, Chaos Mesh, or custom Python-based fault injection). DevOps & Observability: Build and maintain CI/CD pipelines for automated deployments (Jenkins, GitHub Actions, GitLab CI, AWS CodePipeline). Familiarity with DevOps toolchain (CI/CD, Git, Jenkins, GitLab, CodePipeline) . Proficiency in containers & orchestration (Docker, Kubernetes, EKS) . Integrate observability frameworks (Prometheus, Grafana, ELK/EFK, CloudWatch, Datadog) for monitoring and tracing. Strong background in monitoring, observability, and incident management . Apply AWS security best practices for IAM, networking, and data protection. Ensure compliance with internal and external regulatory frameworks (SOC2, ISO, GDPR, etc.). Advanced Python development skills for automation and tooling (Boto3 a must). Experience designing and running chaos experiments (Gremlin, AWS FIS, Litmus, Chaos Mesh, or custom Python-based fault injection). Proficiency in containers & orchestration (Docker, Kubernetes, EKS) . Strong background in monitoring, observability, and incident management . Familiarity with DevOps toolchain (CI/CD, Git, Jenkins, GitLab, CodePipeline) . Knowledge of Go / Shell scripting in addition to Python. Experience with chaos testing in production-like environments . Exposure to multi-cloud or hybrid-cloud environments . Opportunity to lead cloud reliability & chaos engineering initiatives . Growth opportunities through certifications, R&D projects, and leadership roles.

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