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 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: 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 theyre 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.
This position is open to all candidates.