Senior Platform DevOps Engineer

Senior Platform/DevOps Engineer (Kubernetes) Healthcare AI Platform Deployment Role Mission Deploy and operate a prebuilt, Kubernetes-based healthcare analytics/AI platform in a new cloud or on-prem environment using the existing automation (Ansible, Make, Helm). This role requires a deep technical understanding of the codebase's architecture to ensure correct configuration and troubleshoot complex deployment issues. Core Responsibilities The successful candidate will be a hands-on executor focused on standing up one new environment (cloud or on-prem) with repeatable redeployments. · Kubernetes Cluster Integration: Bring up, configure, and integrate a new managed (e.g., EKS) or self-hosted Kubernetes cluster to serve as the foundation for the platform. · Infrastructure Configuration: Adapt and configure all necessary networking and security components: o Ingress controllers and certificates (based on certificates.yml, ingress-controller, and DNS requirements). o DNS and L4/L7 load balancers for internal and external access. · System Component Integration: Configure and integrate essential platform services, including: o Secrets management with Vault. o Identity Provider (IdP) integration, likely Keycloak/OIDC, for user authentication and access controls. o Object storage configuration (MinIO/S3) for the Data Lake. · Build & Deployment Pipeline: o Execute existing build processes (Makefile, containers.yml, charts.yml) to build and push platform component images and Helm charts to container registries. o Set up and maintain the CI/CD pipelines (e.g., *.gitlab-ci.yml) for automated deployment. · Codebase and Logic Interpretation: o Read and interpret the platform’s Python/FastAPI services, Helm charts, and Ansible playbooks to validate system behavior and troubleshoot deployment failures. o Deeply understand what each platform component (api, repository, vdi, data-lake, compute-cluster) does and how they are orchestrated. · System Hardening: Tune storage classes, networking, and security policies, and perform necessary smoke tests and hardening steps before handoff. · Documentation & Handoff: Document all environment-specific steps, configuration details, and create clear operational runbooks and handoff guides. Must-Have Technical Skills · Kubernetes Operations (Expert): Strong operational experience with K8s cluster lifecycle, deploying complex multi-component applications, and using kubectl. · Infrastructure-as-Code (IaC): Proficiency with Terraform for provisioning cloud/on-prem infrastructure and Ansible for configuration management and playbook execution. · Container and Artifact Management: Expertise with container registries, image building, Docker, and the image lifecycle. · Helm: Strong experience with Helm for packaging and deploying Kubernetes applications, including writing and debugging custom charts. · Networking: In-depth knowledge of DNS/TLS, ingress controllers, L4/L7 load balancing, and firewall rules in a cloud and Kubernetes context. · Linux & Shell Scripting: Proficient in Linux system administration and Bash/Shell scripting for automation and diagnostics. · Security Components: Hands-on experience with Vault and setting up Keycloak/OIDC or other identity providers. · Storage: Experience with object storage (S3/MinIO) and configuring Kubernetes persistent volumes (PVs) and storage classes. · Code Literacy: Proven ability to read and reason about Python/FastAPI application code, as well as complex YAML/Helm/Ansible configurations, to validate and troubleshoot system behavior. Nice-to-Have Skills · VDI/remote desktop solutions on Kubernetes (e.g., using VNC or similar technologies as seen in the codebase). · Experience setting up observability (monitoring, logging, tracing). · Experience in regulated environments, such as healthcare or finance. · Ability to implement small fixes or diagnostics in Python/FastAPI. Working Style · A hands-on, bias-for-action executor who prioritizes reusing and adapting existing playbooks and Makefiles over rewriting. · Proactive and meticulous in identifying and addressing environment-specific constraints and dependencies. · Clear and concise documentation skills. · Collaborates effectively with AI/ML tools like Cursor and OpenAI Codex for rapid troubleshooting and code adaptation. Language Fluent in English (written and verbal) for clear documentation and cross-functional collaboration.