Design and build MCP server infrastructure and multi-provider LLM integrations for a global AI platform. Own CI/CD pipelines, automated testing, and distributed systems architecture in a high-velocity startup environment. Requires strong production-grade Golang, hands-on AI/LLM integration experience, and solid AWS expertise.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Nice to Have
Job Description
Senior Backend Engineer – Golang
📍 Amsterdam (hybrid) · Visa sponsorship + relocation support
The company
One of the world's largest technology investors, backing and building a portfolio of 100+ companies across fintech, food delivery, quick commerce and more. You'll join the small engineering team behind their internal AI platform; the infrastructure layer that powers AI-driven products across the entire group. Systems built here reach millions of users worldwide.
The role
This is a build role, not a maintenance one. You'll own the design and delivery of MCP server infrastructure that doesn't exist yet, and the multi-model LLM integrations that connect it to a growing roster of AI providers in production.
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You'll set the architectural patterns rather than follow them. You'll be working in Go, alongside a tight team of engineers and product folks, on the systems that let AI products across the portfolio move fast without breaking. If you're genuinely excited about building agentic AI infrastructure in production (not just calling an API), this is the deep end.
What you'll do
- Design and ship MCP server infrastructure from the ground up
- Build and operate multi-provider LLM integrations in production
- Own CI/CD pipelines, automated testing, and build systems
- Work end-to-end with product and platform teams to get things live
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What we're looking for
- Strong, production-grade Golang
- Genuine hands-on work in the AI/LLM space: integrating models in production, ideally building agentic systems or MCP servers
- Solid AWS, plus distributed systems, microservices, and event-driven thinking
- Ownership of CI/CD and test infrastructure
- Startup / high-velocity DNA: you've shipped fast, owned outcomes, and set the standard
- A bias toward maintainable, well-tested code that holds up at scale
- Event-sourced systems, Kafka / Pub/Sub, or data pipeline experience
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Why this one
Full visa sponsorship and relocation to Amsterdam, a real problem at the frontier of applied AI, and a team that would rather hire three great engineers than six mediocre ones. If you build robust Go services and you're serious about AI infrastructure, this is a rare chance to do it at genuine global scale.
Interested? Let's talk.
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