Site Reliability Engineer

Job Summary We are seeking a highly skilled Site Reliability Engineer (SRE) with expertise in CI/CD pipelines and AI-driven Edge/IoT environments. This role is responsible for ensuring the reliability, scalability, security, and performance of distributed systems across cloud and edge infrastructures while supporting automated deployment of AI/ML applications and services. Key Responsibilities Design, implement, and maintain highly available, scalable, and fault-tolerant systems across cloud and edge environments. Define, monitor, and manage service reliability metrics including SLIs, SLOs, and SLAs. Lead incident response activities, root cause analysis (RCA), and continuous improvement initiatives. Build and maintain observability frameworks including monitoring, logging, and tracing for distributed systems. Architect, implement, and manage CI/CD pipelines for microservices and AI/ML workloads. Automate build, testing, deployment, and release management processes using tools such as Azure DevOps, GitHub Actions, Jenkins, or GitLab CI. Support continuous delivery and over-the-air (OTA) deployment capabilities for edge devices. Integrate security and compliance controls into CI/CD and infrastructure workflows. Deploy, monitor, and manage AI/ML models on Edge and IoT devices. Optimize AI/ML models for edge execution, including performance, latency, and offline functionality. Support secure communication and data flow between cloud platforms and edge devices. Build and manage infrastructure using Infrastructure as Code (IaC) tools such as Terraform, Bicep, ARM, or CloudFormation. Manage containerized workloads using Docker and Kubernetes platforms. Automate infrastructure provisioning, scaling, and configuration management across hybrid environments. Collaborate with cross-functional teams to improve system reliability, scalability, and operational efficiency. Required Qualifications Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent experience. 5+ years of experience in Site Reliability Engineering, DevOps, or Platform Engineering. Strong experience building and managing CI/CD pipelines in production environments. Hands-on experience with Azure cloud services and infrastructure. Experience with containerization and orchestration technologies including Docker and Kubernetes. Proficiency in at least one programming or scripting language such as Python, Go, or Bash. Experience supporting distributed systems and Edge/IoT environments in production. Strong troubleshooting, analytical, and problem-solving skills. Experience with monitoring, logging, and observability solutions. Preferred Qualifications Experience deploying and managing AI/ML models at the edge. Familiarity with MLOps practices including model versioning, monitoring, drift detection, and deployment pipelines. Knowledge of Edge/IoT communication protocols such as MQTT, AMQP, and OPC UA. Experience with real-time streaming and event-driven architectures. Understanding of IoT security concepts including device identity, encryption, and certificate management. Exposure to industrial or operational technology environments such as manufacturing, utilities, or oil and gas.