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Tier-1 brand, mid-level generalist DevOps title, metro location, broad skillset, and popular experience band.
Core DevOps skills are transferable, but banking compliance and MLOps focus increase domain specificity.
Explicit 2–5 year requirement plus mandatory Kubernetes, cloud, CI/CD, and MLOps skills enforce strict technical filtering.
Build and maintain CI/CD pipelines and infrastructure for reliable, secure deployment of AI/ML applications at scale.
Support machine learning model lifecycle including deployment, versioning, retraining, and rollback using containerization and orchestration tools.
Implement monitoring, observability, and security compliance within pipelines and manage hybrid cloud and Kubernetes/OpenShift infrastructure.
2–5 years of DevOps/SRE experience with Python scripting, Kubernetes/Docker, and at least one major cloud platform.
Bachelor’s degree or equivalent experience.
Experience with CI/CD tools such as Jenkins, Tekton, Harness, or GitHub Actions, and infrastructure as code tools like Terraform, Ansible, Helm.
Work Experience Required: 2–5 years as specified in JD.
Able to apply specialized DevOps knowledge with growing autonomy and provide guidance to junior team members.
Experienced managing AI/ML workflows, containerization, and orchestration with tools such as Kubeflow, MLflow, or Airflow.
Strong understanding of security compliance and risk management practices within technology delivery in a regulated environment.