About the role
You'll own Qase's entire infrastructure end-to-end, working directly with our VP of Engineering. We're a 20-person engineering team building a test management platform used by engineering teams worldwide. We currently have one infra engineer — you'll take the lead, set direction, and pragmatically evolve the platform for both internal development and external customers.

What you'll do

• Own and evolve our core stack: Kubernetes (EKS), AWS, Aurora PostgreSQL, ClickHouse
• Drive infrastructure decisions pragmatically — understanding trade-offs between cost, reliability, and speed
• Build and improve our internal platform so engineers can ship faster with full observability
• Design multi-tenant architecture: dedicated clusters, account isolation, cost optimization across AWS accounts
• Improve observability across the stack (monitoring, logging, tracing)
• Support our growing investment in AI agents — infrastructure for agentic systems is becoming a key priority
• Manage the full cycle: CI/CD, infrastructure as code, reliability, security hardening, cost management

What we're looking for

• Strong hands-on experience with AWS (especially EKS, RDS/Aurora), Kubernetes, and Terraform
• Experience with observability tools (Datadog, Grafana, or similar)
• Solid understanding of Linux operations and debugging
• Experience managing multi-cluster or multi-tenant Kubernetes environments
• Track record of making pragmatic infrastructure decisions in startups or scale-ups — not just executing, but designing solutions
• Strong communication skills in English - you'll work directly with the VP of Engineering and across engineering teams

Nice to have

• Experience with ClickHouse or similar OLAP databases
• Go development experience
• Background in B2B SaaS platforms
• Experience with AI/agent infrastructure
• Team lead experience or mentoring junior engineers

What makes this interesting

• Full ownership of infrastructure — no layers between you and decisions
• Direct line to VP of Engineering
• Real architectural challenges: multi-tenant isolation, geo-distribution, cost optimization
• Greenfield opportunity to shape how the platform scales
• Growing AI/agents investment — you'll build the infrastructure that powers it