Site Reliability Engineer

We are looking for a Site Reliability Engineer (SRE) who is strong in Python programming and production engineering. The ideal candidate should have hands-on experience building automation, improving system reliability, troubleshooting production issues, and developing tools/scripts to solve operational challenges at scale. This role is suited for someone who enjoys coding + infrastructure + production problem-solving, rather than a traditional monitoring-focused DevOps role.

Responsibilities:

• Develop and maintain Python-based automation, tools, and services to improve reliability and operational efficiency.
• Write clean, maintainable, and production-grade Python code for automation and infrastructure workflows.
• Troubleshoot complex production issues, perform root cause analysis (RCA), and implement long-term solutions.
• Design and implement solutions for system reliability, scalability, availability, and performance.
• Automate repetitive operational tasks using Python and other scripting technologies.
• Build and improve monitoring, alerting, logging, and observability solutions.
• Work closely with engineering and development teams to identify reliability risks and improve application performance.
• Participate in on-call / production support and handle critical incidents effectively.
• Develop self-healing and automated remediation workflows wherever possible.
• Improve deployment, release, and operational processes through automation.
• Monitor system performance and identify potential bottlenecks, failures, and reliability issues.
• Contribute to capacity planning, incident management, postmortems, and reliability improvements.

Requirements:

• 3-5 years of experience in SRE, Production Engineering, DevOps, Platform Engineering, or a similar role.
• Strong hands-on Python programming experience is mandatory.
• Experience writing production-grade Python code, not just scripting.
• Strong understanding of Linux/Unix systems and troubleshooting.
• Hands-on experience with production systems and incident management.
• Experience with monitoring and observability tools.
• Good understanding of networking, APIs, databases, and distributed systems.
• Experience with CI/CD and automation.
• Familiarity with Docker and Kubernetes.
• Experience with at least one cloud platform such as AWS, GCP, or Azure.
• Strong debugging, problem-solving, and analytical skills.

Good to Have:

• Experience with Terraform / Infrastructure as Code.
• Experience with Prometheus, Grafana, ELK, Datadog, New Relic, or similar observability platforms.
• Experience with AWS/GCP/Azure infrastructure.
• Knowledge of Kafka, Redis, PostgreSQL/MySQL, or other distributed systems.
• Experience building self-healing / auto-remediation systems.
• Understanding of SLOs, SLIs, and SLAs.
• Experience working with high-scale or highly available production environments.
• Strong in Python + Hands-on with Production + Good at Debugging + Automation-oriented + Strong in SRE fundamentals.
• Candidates should have meaningful hands-on experience with Python coding and building production-facing automation/tools.