Site Reliability Engineer (SRE) - Azure focus

Define and implement SLIs / SLOs and error budgets for business-critical digital banking services. Build actionable observability (metrics, logs, traces, dashboards, and alerts) using Dynatrace, Prometheus, Grafana, and ELK, while reducing alert fatigue. Leverage AI-driven insights and anomaly detection (Dynatrace Davis AI or equivalent AIOps platform) to proactively predict and resolve reliability issues before impact. Lead incident management — from on-call triage and root-cause analysis to blameless postmortems with actionable follow-ups. Improve deployment safety with robust rollout / rollback strategies, canary and blue-green deployments, and production readiness reviews. Support and optimize microservices-based architectures, ensuring service reliability, scalability, and inter-service resilience. Conduct capacity planning, performance tuning, and resilience testing, optimizing for both reliability and cost efficiency. Automate operational toil — from runbooks and remediation scripts to proactive health checks and self-healing workflows. Collaborate with DevOps to embed reliability gates and validations into CI / CD pipelines (GitHub Actions, Jenkins, GitLab CI / CD or Azure DevOps). Own and evolve the observability and AIOps stack, driving intelligent automation and predictive alerting capabilities. Maintain high-quality documentation, playbooks, and operational standards across environments. Ensure operational compliance and security alignment with internal controls and regulatory standards. Analyze system performance, availability, and cost data to continually optimize operations. Provide reliability support and escalation guidance for critical production systems during major incidents. Desired Candidate Profile 5+ years of experience in SRE or DevOps roles, building and managing large-scale, high-availability systems across banking, fintech, e-commerce, or other data-intensive digital ecosystems. Bachelor’s degree in Computer Science or equivalent technical experience. Strong experience with Linux environments and performance troubleshooting. Proven expertise in Terraform and Infrastructure as Code (IaC) methodologies. Proficiency with Kubernetes and container orchestration in microservices environments. Hands-on experience with AWS (preferred); exposure to Azure or GCP is an advantage. Deep knowledge of Dynatrace (AIOps, Davis AI), Prometheus, Grafana, and the ELK stack. Experience implementing AI / ML-driven reliability or automation solutions (AIOps, anomaly detection, predictive alerting). Practical understanding of CI / CD pipelines (GitHub Actions, Jenkins, GitLab CI / CD or Azure DevOps). Experience with Kafka, RabbitMQ, Redis, Aurora, and RDS databases. Strong scripting or programming skills in Python, Bash, or Go. The Ideal Candidate Organized, structured, and meticulous in approach. Experienced in cross-functional collaboration and working with distributed teams. Strong analytical mindset with excellent troubleshooting skills for complex production systems. Calm and composed communicator under pressure, capable of leading during high-impact incidents. Proactive problem-solver who anticipates issues and drives preventive improvements. Passionate about AI-driven automation, observability, and reliability engineering. Continuously learning, keeping up-to-date with cloud-native, microservices, and SRE best practices. A collaborative and adaptable team player who thrives in a fast-paced, regulated environment and is passionate about building reliable, scalable systems that empower digital banking innovation. Skills SRE Dynatrace Kubernetes Employment Type Full-time