DevOps Deployment Engineer

About the Role

Work directly with Tier-1 customers, deploy our platform in their Kubernetes and OpenShift environments, and solve whatever stands in the way, from infrastructure and networking to identity integrations.

Key Responsibilities

• Deploy the Jeen.ai platform in customer Kubernetes and OpenShift environments, both on-prem (including air-gapped and GPU environments) and in the cloud.
• Troubleshoot and resolve deployment and runtime issues, working across the application, container, and infrastructure layers.
• Diagnose networking problems end to end: DNS, ingress and routes, load balancers, firewalls, proxies, TLS certificates, and network policies.
• Integrate the platform with customer identity providers (Active Directory, Azure AD/Entra ID, Okta, Keycloak) over SAML, OIDC, and LDAP.
• Own the full implementation lifecycle: installation, integration, customization, and post-deployment support.
• Work directly with IT, security, and infrastructure teams at banks, defense organizations, and other regulated enterprises.
• Feed field insights back to R&D and Product to improve our deployment process and documentation.

Requirements

• 2 + years of hands-on experience in Professional Services, DevOps, Systems, or Integration roles.
• Deep, hands-on Kubernetes experience, including troubleshooting production environments.
• Hands-on experience with OpenShift
• Strong Helm skills, including customizing and troubleshooting charts.
• Strong Docker and container experience, including working with private registries.
• Solid networking knowledge: TCP/IP, DNS, TLS/certificates, proxies, load balancing, and firewalls.
• Hands-on experience integrating with IDPs using SAML, OIDC, or LDAP.
• Strong Linux skills and scripting (Bash or Python).
• Strong ownership, seeing problems through until they’re solved.
• Clear communication with enterprise customers, including under pressure.
• High-level English, written and spoken.

Preferred Qualifications

• Hands-on experience with at least one major cloud provider (AWS, Azure, or GCP), including managed Kubernetes services such as EKS, AKS, or GKE.
• Air-gapped or offline Kubernetes installations.
• NVIDIA GPU environments.
• Exposure to LLMs, RAG, or AI/ML workloads.
• Experience in highly regulated environments.
• Relevant certifications.