
Site Reliability Engineer
4 days ago
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.
Key Responsibilities
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.
- Implement self-healing and resilience-focused automation scripts.
Chaos Engineering & Resiliency:
- Design and execute chaos experiments (fault injection, latency, outages, resource failures) to validate system resilience.
- 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).
- Partner with SRE and development teams to define SLIs, SLOs, and error budgets .
- Document learnings from chaos tests and improve incident response & recovery playbooks.
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) .
- Good understanding of resilient architectures, reliability principles, and disaster recovery
- Integrate observability frameworks (Prometheus, Grafana, ELK/EFK, CloudWatch, Datadog) for monitoring and tracing.
- Ensure proactive alerting and real-time visibility into system health.
- Strong background in monitoring, observability, and incident management .
Security & Compliance:
- Apply AWS security best practices for IAM, networking, and data protection.
- Ensure compliance with internal and external regulatory frameworks (SOC2, ISO, GDPR, etc.).
Required Skills & Qualifications
- 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).
- Solid knowledge of IaC (Terraform / CloudFormation) .
- 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) .
- Good understanding of resilient architectures, reliability principles, and disaster recovery .
Preferred Skills
- 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 .
- Strong problem-solving and debugging skills.
What We Offer
- Opportunity to lead cloud reliability & chaos engineering initiatives .
- Culture focused on automation, resilience, and continuous improvement .
- Growth opportunities through certifications, R&D projects, and leadership roles.
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