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Mid-level DevOps role, metro location, broad skillset and recognizable engineering brand drive high competition.
Core DevOps/SRE skills are transferable but AI-enabled AIOps and specific tooling increase domain specificity.
Explicit 5-10 years plus extensive mandatory DevOps, cloud, and security tooling expectations make screening strict.
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Design and deliver scalable AI-powered DevOps and AIOps solutions to improve mean time to recovery (MTTR) and automate incident resolution for large enterprises.
Develop, optimize, and automate MLOps pipelines and cloud infrastructure using Terraform, CloudFormation, Kubernetes, Python, and Shell scripting.
Drive Site Reliability Engineering (SRE), DevSecOps practices, and ensure ITSM integration and compliance across enterprise-scale environments.
5 to 8 years of enterprise-level DevOps engineer experience with AI-enabled cloud engineering focus.
Bachelor of Technology (BTech) or equivalent in Computer Science or Electronics & Communication.
Proficiency in Kubernetes, Terraform, Docker, Python, Shell scripting, and experience with CI/CD tools (e.g., Jenkins, GitLab CI).
Experience with container orchestration (Kubernetes/OpenShift), Infrastructure-as-Code (Terraform, Ansible), and monitoring tools (Prometheus, Grafana, ELK).
Experienced in building AI-driven automation frameworks and enterprise-grade AIOps platforms enhancing operational efficiency and resilience.
Strong background in container orchestration, service mesh technologies (Istio, Linkerd), and secure DevOps with policy-as-code and vulnerability scanning tools.
Skilled in integrating Cloud cost optimization (FinOps), SRE principles, and security automation into scalable DevOps workflows.