AI / ML Engineer (Agent Developer)

Job Description Essential Job Functions: - Design, implement, and maintain automated CI/CD pipelines to support secure and reliable application delivery across multiple repositories and environments. - Manage and optimize Kubernetes-based platforms, including cluster operations, deployments, Helm chart management, scaling, and environment isolation. - Establish and maintain GitOps deployment practices, container registry management, and automated application lifecycle processes. - Configure and support networking components, including API gateways, ingress controllers, TLS certificates, DNS integration, and network security policies. - Implement secure infrastructure services, including secrets management, managed identities, and controlled execution environments for modern cloud-native applications. - Deploy and maintain AI agents and MCP server components using standardized automation frameworks, reusable templates, and platform tooling. - Collaborate with development, security, and operations teams to ensure scalable, secure, and highly available cloud infrastructure solutions. Basic Qualifications - Bachelor's degree in Computer Science, Information Technology, Engineering, or equivalent combination of education and experience. - Typically, 3+ years of professional experience in DevOps, Site Reliability Engineering (SRE), Cloud Engineering, or related infrastructure roles. - Hands-on experience managing Kubernetes platforms such as Azure Kubernetes Service (AKS), Amazon EKS, or equivalent container orchestration environments. - Strong knowledge of Helm, container orchestration, and cloud-native application deployment practices. - Experience with Azure cloud services, including Azure Container Registry (ACR), Azure Key Vault, Blob Storage, and container-based compute services. - Proven experience designing and maintaining CI/CD pipelines using Azure DevOps, GitHub Actions, or comparable automation platforms. - Expertise in Docker containeriz