Candidate should have 7-8 years experience with below skills :

Engineering Skills

1. Mastery of GitOps and DevSecOps approaches with a security-by-design mindset.

2. Experience deploying in highly secure on-premise and air-gapped environments.

3. Practice in Agile/Iterative working methods including security and architecture reviews.

4. Implementation of systems reliability through SLO/SLI and resilience testing.

5. Capability to manage end-to-end observability from cloud to on-premise environments.

6. Ability to integrate AI pipelines and datasets into DevSecOps chains.

7. Strong engineering culture focused on automation, quality, and technical standards.

Technical Skills

1. Proficiency in containers and orchestration using Kubernetes, Docker, Helm, and Kustomize.

2. Expertise in hybrid CI/CD tools (GitLab CI/Jenkins) and artifact registries like Harbor or Artifactory.

3. Mastery of automation tools including Terraform, Ansible, and Puppet.

4. Strong proficiency in programming and scripting with Bash, Python, or Go.

5. Knowledge of secure supply chain tools such as SBOM, image signing, and OPA/Gatekeeper.

6. Management of security and identities including PKI, mTLS, Secrets, and RBAC.

7. Management of GPU planning (NVIDIA device plugin) for industrializing AI workloads.