24 geprüfte Remote KI-Jobs in Integration & Automatisierung

Anforderungen

Strong software engineering fundamentals: you design clean abstractions, write maintainable code, and can justify your architecture choices, not just make something work. You re a generalist who is as comfortable debugging a distributed system as designing an auth flow or tuning an agent s behavior. - Production experience with Go is strongly preferred; candidates without Go should demonstrate strong systems programming skills in a comparable language. - Experience building or operating large-scale SaaS platforms in production: multi-tenant systems, high volumes, and the failure modes that only show up at scale. - Solid understanding of Kubernetes. Our entire platform runs on it, and the assistants we build answer questions about it.

You should be at home with autoscaling, scheduling, and networking concepts. - You ve personally driven a complex project end-to-end. - Hands-on experience with AI coding agents and agentic development workflows. This is how we build, not just what we build. - You ve used observability tooling in production. - CI/CD and DevOps practices experience. - Strong English skills, both verbal and written. - Startup mindset: adaptable, proactive, and comfortable with ambiguity. What will make you stand out - You ve built agentic systems that shipped: MCP servers or clients, agent gateways, tool-use orchestration, RAG pipelines, evaluation frameworks, and you can talk about what broke in production and how you found out.

This is the single biggest differentiator for our team. - Deep hands-on experience with one or more of AWS, GCP, or Azure, with real understanding of IAM, compute, networking, and their APIs, not just console-level usage. - Experience with LLM application quality: evaluations, prompt engineering at scale, latency and cost optimization of agent loops. - Knowledge of OAuth 2.0 / OIDC and multi-tenant authorization design. - Deep knowledge of EKS, GKE, or AKS internals. - Kubernetes or cloud-native OSS contributions. Responsibilities - Design and build the systems behind our AI assistant: agent flows, context retrieval, and the data connections that let it reason about live Kubernetes infrastructure. - Build and evolve our public, permission-aware MCP server: curated tools, identity, audit, and strict safety gates, so customers can use CAST AI from their own AI clients. - Develop and maintain cloud connectivity across AWS, GCP, and Azure, and the data foundations our agents build on. - Write production Go services that interact with cloud provider APIs, the Kubernetes control plane, and LLM APIs in real time. - Own features end-to-end: from design through implementation, testing, and production rollout (most projects ship in 1 to 4 weeks). - Debug novel problems: an agent giving a wrong answer, a cross-cloud permission edge case, a data freshness issue that only appears at scale. - Build the quality harness: evals, telemetry, feedback loops, that let us ship agent improvements without regressions. - Contribute to product direction and backlog. Shape what gets built next, not just how it s built. - Participate in the team s on-call rotation.

Tools We Use Daily - Programming Languages: Go - AI & Agents: MCP (servers and clients), agent gateways, LLM provider APIs, RAG, evaluation pipelines - Cloud & Orchestration: Kubernetes, AWS, GCP, Azure - Infrastructure as Code: Terraform - Databases & Storage: PostgreSQL, Cloud Object Storage, ClickHouse - Workflows & APIs: Temporal, GCP Pub/Sub, gRPC, REST - Observability & Product Analytics: Prometheus, Grafana, Loki, Tempo, PostHog - CIGitHub CI with ArgoCD and Kargo What s in it for you? - Competitive salary (€6,500 to €9,000 gross, depending on the level of experience) - Work on genuinely new problems: production MCP platforms and AI assistants for Kubernetes and cloud infrastructure are not solved domains. You ll be defining them, not following a playbook. - Equity options. - Real users, fast: your work ships to hundreds of organizations in weeks, not quarters. - Enjoy a flexible, remote-first global environment. - Collaborate with a global team of cloud experts and innovators, passionate about pushing the boundaries of Kubernetes technology. - Spend 10% of your work time on personal projects or self-improvement. - Learning budget for professional and personal development, including access to international conferences and courses. - Annual hackathon to spark new ideas and strengthen team bonds. - Team-building budget and company events to connect with your colleagues. - Equipment budget to ensure you have everything you need. - Extra days off to help maintain a healthy work-life balance. Hiring process - Screening call with Recruiter - Hiring Manager interview - Technical interview (system design) - Live coding - Culture Check interview with an executive As part of our standard hiring process, a background check may be conducted at the final stage of recruitment through our third-party provider, Checkr.

Please note that Cast AI does not provide any form of visa sponsorship/work permit. #LI-Remote

Zur Position

What you ll be solving A platform engineer opens their AI client of choice, connects it to CAST AI, and types: Why did our spend jump 40% in eu-west last week? Thirty seconds later they have an answer, pulled from live cluster state and cost data, with links back to the evidence. No dashboards.

No YAML archaeology. Just a question and a correct, permission-checked answer. Your job is to make that interaction boring.

Reliably, securely, at production scale. Behind it sits the hard part: an AI assistant that reasons over thousands of production Kubernetes clusters, a platform that safely exposes company infrastructure to external AI clients, and quality pipelines that tell us when the agent is wrong before a customer does. Get it right, and operators stop clicking through consoles entirely.

Get it wrong once, and an agent gives a confidently wrong answer to someone managing production. CAST AI already runs Kubernetes infrastructure autonomously. Our automation makes thousands of cost-and-reliability decisions a day.

Cast Pilot is the team building the intelligence layer on top of that: AI assistants for Kubernetes and the cloud itself. Our assistant already answers thousands of questions a month from hundreds of organizations. Now we re opening the platform up: a public, permission-aware MCP server so customers can plug CAST AI straight into their own AI clients and agents, deeper connectivity across all three major clouds (AWS, GCP, Azure), and a continuous push to make our agents smarter, better grounded, and more capable.

This is greenfield AI platform work on top of battle-tested infrastructure. Most features ship in 1 to 4 weeks. This is a location-specific opportunity.

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.