DevOps/Devsecops Engineer

Key Responsibilities Cloud Infrastructure & Automation Design, deploy, and maintain cloud environments on AWS or GCP. Develop and manage infrastructure using Infrastructure-as-Code tools such as Terraform or similar technologies. Implement secure networking architectures, including VPCs, private connectivity, VPNs, peering, and network segmentation. Establish scalable multi-environment and multi-account cloud strategies. Container Platform & Kubernetes Build and manage Kubernetes environments for production workloads. Configure cluster security, RBAC, autoscaling, workload isolation, and governance controls. Create standardized deployment frameworks for microservices, backend services, and AI-related workloads. Support both real-time and batch processing environments. CI/CD & Release Automation Design and optimize CI/CD pipelines to streamline software delivery. Implement automated testing, deployment validation, and release management processes. Support deployment strategies such as blue-green, canary, and phased rollouts. Improve developer productivity through automation and deployment standardization. Observability & Site Reliability Implement monitoring, logging, tracing, and alerting solutions. Define service reliability metrics, performance objectives, and operational standards. Support incident response processes, root-cause analysis, and continuous service improvement. Develop operational runbooks and support on-call readiness. Security & DevSecOps Strengthen cloud security through identity and access management best practices. Manage secrets, certificates, and sensitive configuration securely. Implement vulnerability scanning, dependency analysis, and container security controls. Enforce security policies through automation and governance frameworks. Support audit readiness and compliance requirements. AI/ML Platform Support Collaborate with data science and machine learning teams to operationalize AI solutions. Support model deployment, inference services, batch processing, and ML infrastructure. Monitor performance, availability, and resource consumption of AI workloads. Contribute to platform capabilities that improve AI product scalability. Cost Optimization Monitor cloud spending and resource utilization. Implement tagging, budgeting, and optimization initiatives. Drive efficiency improvements without compromising performance or reliability. Developer Experience Build self-service infrastructure capabilities and reusable engineering templates. Improve internal tooling and automation workflows. Maintain clear technical documentation and operational guidelines. Help create a smooth developer experience across engineering teams. Requirements Essential Skills & Experience Minimum 4 years of experience in DevOps, Site Reliability Engineering, Platform Engineering, or related infrastructure roles. Strong hands-on experience with AWS or Google Cloud Platform. Proven expertise with Infrastructure-as-Code tools, preferably Terraform. Solid Kubernetes administration and containerization experience (Docker, Helm, Kustomize, etc.). Strong knowledge of CI/CD pipelines and modern software delivery practices. Good understanding of Linux systems, networking, and automation scripting using Python and/or Bash. Experience implementing monitoring, logging, and observability solutions. Strong understanding of cloud security principles, IAM, secrets management, and infrastructure hardening. Ability to collaborate effectively with software engineers, product stakeholders, and technical leadership. Strong documentation and communication skills. Preferred Qualifications Experience with GitOps practices and tools such as ArgoCD or Flux. Exposure to policy-as-code and infrastructure testing frameworks. Familiarity with data engineering or machine learning ecosystems. Experience working with distributed systems, streaming platforms, or large-scale data processing technologies. Knowledge of enterprise compliance, governance, and security review processes. Exposure to reliability engineering practices such as resilience testing or disaster recovery exercises.