* Build and maintain cloud infrastructure components across AWS, Azure, GCP, or equivalent cloud platforms under the guidance of senior platform architects.
* Implement infrastructure-as-code using Terraform, OpenTofu, cloud-native templates, or equivalent frameworks.
* Build and maintain CI/CD pipelines for application services, AI agents, data pipelines, infrastructure changes, and environment promotions.
* Support GitOps-based deployment workflows using tools such as Argo CD, Flux, GitHub Actions, GitLab CI/CD, Azure DevOps, or equivalent platforms.
* Containerize application services, Python-based AI agents, data services, and supporting platform components using Docker.
* Deploy and manage workloads on Kubernetes platforms such as EKS, AKS, GKE, enterprise Kubernetes distributions, or customer-managed clusters.
* Create, update, and troubleshoot Helm charts, values files, environment-specific configurations, secrets injection, and rollback procedures.

* Hands-on experience with at least one major cloud platform: AWS, Azure, or GCP.
* Practical experience with Terraform, OpenTofu, or equivalent infrastructure-as-code frameworks.
* Experience with CI/CD tools such as GitHub Actions, GitLab CI/CD, Azure DevOps, Jenkins, or equivalent platforms.
* Working knowledge of Docker, Kubernetes, Helm, and containerized workload deployment.
* Familiarity with Kubernetes concepts such as deployments, services, ingress, config maps, secrets, namespaces, RBAC, and resource management.

As a DevOps / Cloud Engineer, you will help build, automate, deploy, monitor, and operate the cloud infrastructure for our AI and data platform. You will work with senior platform architects, AI/ML engineers, data engineers, and product teams to support reliable deployments across cloud, hybrid, and enterprise customer environments.
This is a hands-on engineering role for someone who is comfortable working with cloud platforms, containers, CI/CD pipelines, infrastructure-as-code, observability, and secure deployment practices. The role is ideal for an engineer who wants to build production-grade platform capabilities for an enterprise AI product.