Site Reliability Engineer (SRE)

About the role

The Site Reliability Engineer will define and implement service level indicators and objectives for critical digital banking services, build robust observability, and use AI‑driven insights to anticipate issues. You will lead incident management, improve deployment safety, and automate operational toil while collaborating closely with DevOps teams.

Key responsibilities

• Define and implement SLIs/SLOs and error budgets for critical digital banking services.
• Build and maintain observability stack (metrics, logs, traces, dashboards, alerts) using Dynatrace, Prometheus, Grafana and ELK.
• Leverage AI‑driven anomaly detection to predict and resolve reliability issues before impact.
• Lead incident management, from on‑call triage to blameless post‑mortems and actionable follow‑ups.
• Design and operate safe deployment strategies such as canary, blue‑green, rollout/rollback and production readiness reviews.
• Support microservices architecture, conduct capacity planning, performance tuning and resilience testing.
• Automate operational toil with runbooks, remediation scripts and self‑healing workflows.
• Collaborate with DevOps to embed reliability gates into CI/CD pipelines (GitHub Actions, Jenkins, Azure DevOps, etc.).

Required profile

• 5+ years of experience in SRE or DevOps roles within banking, fintech or other data‑intensive domains.
• Bachelor’s degree in Computer Science or equivalent technical experience.
• Strong Linux background and performance troubleshooting skills.
• Proven expertise with Terraform, IaC and Kubernetes container orchestration.
• Hands‑on experience with AWS (preferred) and exposure to Azure or GCP.
• Deep knowledge of Dynatrace, Prometheus, Grafana and the ELK stack.
• Experience implementing AI/ML‑driven reliability or automation solutions.
• Excellent analytical mindset, calm communication under pressure and collaborative attitude.

Required skills

• Go, Python, Bash
• AWS, Azure, GCP
• Terraform, Kubernetes
• Dynatrace, Prometheus, Grafana, ELK
• Kafka, RabbitMQ, Redis, Aurora, RDS
• GitHub Actions, Jenkins, Azure DevOps
• AI‑driven anomaly detection, predictive alerting