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Salary: EUR 6,500 - 9,000 / monthly
Cast AI is an automation platform that operates cloud-native and AI infrastructure at scale. The company embeds autonomous decision-making directly into Kubernetes and cloud environments to continuously optimize performance, reliability, and efficiency in production. Over 2,100 companies rely on Cast AI, including Akamai, BMW, Cisco, FICO, HuggingFace, NielsenIQ, Swisscom, and TGS. Cast AI achieved unicorn status in January 2026 with a valuation exceeding $1 billion.
This role is part of the Product Foundations team, which owns the trust-and-accounting layer underlying the entire platform. The team works on authentication, authorization, and SSO for every user and workload; billing, audit trails, notifications, and feature flags that keep the platform transparent; real-time cloud pricing tracking across every region and availability zone, including Spot availability and discounts; and reporting that turns high-volume time-series data into fast, accurate answers about automation savings.
Key responsibilities include:
- Design, build, and operate backend services in Go that other teams and customers depend on being correct
- Own features end-to-end: from design through implementation, testing, and production rollout
- Debug complex production issues involving security-, money-, or trust-critical flows
- Collaborate with product and other engineering teams to solve problems without textbook solutions
- Contribute to product direction and backlog—shape what gets built next, not just how it's built
The role uses Go, Kubernetes, AWS/GCP/Azure, Terraform, PostgreSQL, ClickHouse, GCP Pub/Sub, gRPC, REST APIs, Prometheus, Grafana, Loki, Tempo, and GitLab CI with ArgoCD. The team operates in a fast-paced environment where most feature projects are completed in 1 to 4 weeks. On-call participation is required for some teams, with separate compensation provided.
Requirements:
- Strong software engineering fundamentals: design clean abstractions, write maintainable code, and justify architecture choices
- Production experience with Go strongly preferred; candidates without Go must demonstrate strong systems programming skills in a comparable language
- Experience building or operating trust-critical systems at scale—authentication/authorization, billing, or financial/accounting-adjacent data where being wrong has real consequences
- Good understanding of API design best practices: versioning, backward compatibility, auth, idempotency, async patterns
- Strong debugging, optimization, and performance-tuning skills, including query profiling, index design, and database performance tuning beyond ORM usage
- Experience operating and optimizing systems under high load; ability to find and fix bottlenecks rather than just add resources
- Hands-on experience with Kubernetes: understand core concepts (pods, services, deployments) and have deployed or debugged something on a cluster
- Experience with AI coding agents and agentic development workflows
- Personally driven a complex project end-to-end
- Strong English skills, both verbal and written
- Startup mindset: adaptable, proactive, comfortable with ambiguity
- Participate in on-call rotation for teams that require it
Nice-to-haves:
- Multi-tenant identity system design (authentication, authorization, SSO)
- Enterprise identity protocols (SAML, OIDC, SCIM)
- Billing, audit-trail, notification, or feature-flag systems in production
- Experience with cloud provider pricing/billing APIs across AWS, GCP, or Azure, or tracking Spot instance availability
- High-cardinality time-series ingestion and querying at scale
- Understanding of Kubernetes internals
- CI/CD and DevOps practices experience
- Observability tooling (Prometheus, Grafana, OpenTelemetry) in production
