Site Reliability Engineer

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.