Platform Engineer (Kubernetes / Cloud / Distributed Systems)
HybridBerlin, State of Berlin, Germany
Job Summary
Design and build a control plane to provision dedicated customer environments using infrastructure as code with Terraform or Pulumi. Implement Kubernetes-based platforms for isolated workloads and design high-density isolation strategies to ensure strict data separation. Manage and optimize distributed database stacks including relational, vector, and graph databases while implementing auto-scaling systems for compute-intensive AI workloads. Build APIs and platform tooling for deployment and orchestration, maintain CI/CD pipelines, and ensure security, compliance, and reliability of infrastructure. This role focuses on Kubernetes, infrastructure automation, and multi-tenant architecture supporting high-performance AI workloads for a startup building a next-generation memory engine and data platform for AI agents.
Required Qualifications
- Strong experience with AWS, Azure, or GCP
- Deep experience with Kubernetes (Operators, CRDs, service meshes)
- Experience building single-tenant or multi-tenant SaaS platforms
- Experience operating distributed databases at scale (PostgreSQL, Vector DB, or Graph DB)
- Proficiency in Go, Python, or Rust
- Experience designing REST or GraphQL APIs
- Strong experience with CI/CD and infrastructure automation
- Solid understanding of security best practices and compliance standards
Desired Qualifications
- Experience with vector databases or AI infrastructure
- Experience with graph databases such as Neo4j
- Experience working in fast-growing startups or open-source environments
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