System Reliability Engineer (Platform)

About the Role

System Reliability Engineer (Platform) responsible for operating and improving the platform that runs AKS clusters, API gateways, and AI services.

Responsibilities

• Monitor, maintain, and optimize Azure Kubernetes Service (AKS) cluster health, availability, and performance.
• Define and track Service Level Objectives (SLOs), Service Level Indicators (SLIs), and error budgets for all platform services.
• Lead incident response across L1 (automated detection and recovery), L2 (root cause investigation), and L3 (deep engineering resolution); produce post-mortem documentation for P1/P2 incidents.
• Implement and enforce cluster security policies, resource quotas, and namespace governance.
• Manage the central API gateway including authentication policies, rate limiting, blue-green traffic routing, and request monitoring; ensure zero-downtime deployments with instant rollback capability.
• Operate the central abstraction layer for Azure OpenAI and Azure AI Services — model version control, endpoint configuration, usage monitoring, and reliability mechanisms (retry, fallback, failover).
• Monitor AI service usage and API traffic patterns; detect anomalies, adjust configurations proactively, and maintain SLAs for platform-managed AI services.
• Build and maintain an observability stack covering API metrics, resource metrics, log standards, and distributed tracing across platform services.
• Develop dashboards and alerting mechanisms across all support tiers; every alert must include service name, error type, likely cause, and trace ID.
• Establish and maintain runbooks for L1 triage, L2 escalation, and L3 resolution across all critical platform components.
• Design, implement, and maintain CI/CD pipelines using Jenkins and Azure DevOps for automated deployment of data and AI services.
• Enforce code quality, testing standards, and deployment governance through pipeline automation.
• Manage Kubernetes-based application deployments across UAT and production environments.
• Monitor and optimize cloud resource utilization and spending across Azure services; conduct capacity planning and implement resource tagging, cost allocation, and rightsizing recommendations.

Qualifications

• Bachelor's degree or higher in Computer Science, Information Technology, Software Engineering, or a related field.
• 5+ years of hands-on experience in data engineering, platform engineering, DevOps, or SRE roles.
• Demonstrated experience operating Kubernetes clusters in production environments, preferably on Azure (AKS).
• Experience handling platform support across L1 (automated monitoring & recovery), L2 (escalation & triage), and L3 (deep engineering & resolution) tiers.
• Experience with API gateway management in a microservices environment is advantageous.
• Experience in a financial services or regulated environment is advantageous.

Skills

• Required: Python, Bash/shell scripting, Jenkins, Azure DevOps, observability and monitoring (metrics, logs, distributed tracing), Kubernetes (AKS), CI/CD pipeline design and automation.
• Preferred: Helm & Kubernetes manifests, API gateway platforms (Kong, NGINX, Azure API Management), Azure OpenAI or equivalent AI service operations, Terraform or equivalent IaC, Azure CLI, Databricks workspace administration.