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.