Site Reliability Engineer

Role & responsibilities

Strong experience in Site Reliability Engineering, DevOps, Platform Engineering, or Infrastructure Engineering roles, preferably supporting enterprise SaaS platforms
Deep technical expertise with Microsoft Azure, including hands-on experience with Azure compute (VMs, App Services, AKS), networking (VNets, Load Balancers, Application Gateway), storage (Blob Storage, Azure Files), and Azure SQL/Cosmos DB Proficiency in at least one programming or scripting language (Python, Go, Bash, PowerShell) for building automation tools and infrastructure management Hands-on experience with containerization and orchestration technologies, particularly Docker and Kubernetes Solid understanding of monitoring and observability tools (e.g., Prometheus, Grafana, Azure Monitor, Application Insights, ELK stack, or similar) Experience with CI/CD pipelines and tools such as Azure DevOps, GitHub Actions, GitLab CI, or Jenkins Strong troubleshooting and problem-solving skills with the ability to diagnose complex issues across multiple layers of the stack (network, infrastructure, application, data) Understanding of distributed systems, high-availability architectures, load balancing, and fault tolerance patterns Excellent communication skills with the ability to explain technical concepts to both technical and non-technical audiences, document solutions clearly, and collaborate effectively across teamsAlso helpful, but not required Strong experience with infrastructure-as-code tools such as Terraform, ARM templates, Bicep, or similar technologies Experience with data platforms, streaming architectures, ETL/ELT pipelines, or analytics infrastructure (e.g., Apache Kafka, Azure Event Hubs, Azure Stream Analytics, Azure Data Factory, Databricks) Background in software development or data engineering with understanding of how data-intensive applications are built and deployed Experience supporting IoT platforms, industrial systems, or manufacturing technology Knowledge of AI/ML infrastructure, model serving, and supporting production ML workloads Experience with security and compliance frameworks relevant to enterprise SaaS platforms Azure certifications (e.g., Azure Administrator, Azure Solutions Architect, Azure DevOps Engineer Expert) Familiarity with chaos engineering, performance testing, and reliability practices such as SRE principles from Google or similar frameworks Experience working in global support organizations with distributed teams and 24/7 on-call responsibilities