Senior Software Engineer, AI Agents & Cloud Platform
New
C
CAST AICloud infrastructure
We are currently accepting applications from candidates residing in the following European countries: Bulgaria, Croatia, Estonia, Greece, Hungary, Latvia, Lithuania, Poland, Romania, Slovakia, Cyprus, Malta, Finland, Sweden, Ireland, Moldova, North Macedonia, Montenegro, Slovenia, and Ukraine.Full-TimeSenior
SalaryCompetitive salary (€6,500 to €9,000 gross, depending on the level of experience)
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Job Details
- Languages
- Strong English skills, both verbal and written.
- Required Skills
- AWSGCPKubernetesGoCI/CDDevOps
Requirements
- Bring strong software engineering fundamentals, including clean abstractions, maintainable code, and the ability to justify architecture choices.
- Have production experience with Go, or demonstrate strong systems programming skills in a comparable language.
- Have experience building or operating large-scale SaaS platforms in production, including multi-tenant systems and high-volume environments.
- Have a solid understanding of Kubernetes, including autoscaling, scheduling, and networking concepts.
- Have personally driven a complex project end-to-end.
- Have hands-on experience with AI coding agents and agentic development workflows.
- Have used observability tooling in production.
- Have experience with CI/CD and DevOps practices.
- Have strong verbal and written English skills.
- Be adaptable, proactive, and comfortable with ambiguity.
Responsibilities
- Design and build AI assistant agent flows, context retrieval, and data connections for reasoning about live Kubernetes infrastructure.
- Build and evolve the public, permission-aware MCP server, including curated tools, identity, audit, and safety gates.
- Develop and maintain cloud connectivity across AWS, GCP, and Azure and the data foundations used by agents.
- Write production Go services that interact with cloud provider APIs, the Kubernetes control plane, and LLM APIs.
- Own features from design through implementation, testing, and production rollout.
- Debug agent-answer errors, cross-cloud permission edge cases, and data freshness issues at scale.
- Build evaluations, telemetry, and feedback loops to ship agent improvements without regressions.
- Contribute to product direction and backlog.
- Participate in the team's on-call rotation.
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