> Markdown version of [/jobs/ext/15971-senior-infrastructure-engineer-ai-platform](https://www.wearedevelopers.com/jobs/ext/15971-senior-infrastructure-engineer-ai-platform). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Infrastructure Engineer, AI platform - **Company:** Prosus - **Location:** Amsterdam, Netherlands - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Automation of Tests, Python (Programming Language), Systems Integration, Large Language Models, AI Platforms, Kubernetes, Ripple (payment Protocol), Build Tools, Terraform - **Published:** May 24, 2026 - **Apply:** https://nl.indeed.com/viewjob?jk=4fab95bde71f3c5c ## About the Role Do you have experience in Terraform?, Do you have a Master's degree?, You think in systems. When a product team says "we need this to work across 12 companies," you're already mapping the architecture - where the shared patterns live, where the edge cases break, and what guardrails will keep things coherent as the footprint grows. You're comfortable making architectural calls with 60 to 80 percent of the information, then iterating quickly when the evidence shifts. You hold strong opinions on infrastructure quality but stay low-ego about how you get there. You've seen what happens when platform standards erode at scale, and you take ownership of preventing it - not because someone asked you to, but because it matters. Ambiguity doesn't slow you down - it's where you do your best work., * Deep hands-on AWS expertise across compute, networking, storage, and managed services - you know which service to reach for and why * Proven track record of scaling infrastructure for AI or ML workloads in production, where reliability and latency are non-negotiable * Strong command of infrastructure-as-code - Terraform, CDK, or equivalent - applied at real scale, not just in greenfield projects * Experience operating in a multi-product or platform-team context, where your decisions ripple across multiple engineering teams and products * Proficiency in Go (5+ years), with a track record of building and operating production backend services; Python is a bonus * Hands-on experience integrating with multiple AI and LLM providers in production - you understand how model capabilities translate into robust, scalable backend systems * Comfortable owning CI/CD pipelines, automated test infrastructure (unit, integration, E2E), and build systems end-to-end * Systems-level thinking - you design for reliability, scalability, and performance from the start, not as an afterthought * Comfortable defining and enforcing infrastructure standards and guardrails - you've set the bar for a team, not just met it * Experience with LLM serving infrastructure - vLLM, Triton, SageMaker, or similar - is a strong plus * Familiarity with Kubernetes and container orchestration at scale is a plus * Experience building and maintaining event-sourced systems is a plus * Direct experience building MCP servers or working with Model Context Protocol is a plus ## Related Videos - [Shipping Faster with Less: Render on Cloud Hosting, AI Workloads, and the Future of DevOps](https://www.wearedevelopers.com/videos/1894-shipping-faster-with-less-render-on-cloud-hosting-ai-workloads-and-the-future-of-devops) - [Infrastructure as Code: The Developer's Secret Weapon](https://www.wearedevelopers.com/videos/1221-infrastructure-as-code-the-developer-s-secret-weapon) - [Understanding Kubernetes in a visual way](https://www.wearedevelopers.com/videos/100085-understanding-kubernetes-in-a-visual-way) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) - [Implementing Feature Environments with AWS and Terraform](https://www.wearedevelopers.com/videos/531-implementing-feature-environments-with-aws-and-terraform) - [Instant KAI Sandboxes with vCluster: Multi-Tenant, Multi-Scheduler GPU Sharing](https://www.wearedevelopers.com/videos/100333-instant-kai-sandboxes-with-vcluster-multi-tenant-multi-scheduler-gpu-sharing) ## Related Articles - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [From Prototype to Production: Build AI Agents with This Free 4-Course Learning Path](https://www.wearedevelopers.com/magazine/655-from-prototype-to-production-build-ai-agents-with-this-free-4-course-learning-path) - [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Dev Digest 121 - AI goes offline](https://www.wearedevelopers.com/magazine/456-dev-digest-121-ai-goes-offline)