GenAI Platform Engineer - Madrid OR Amsterdam

GenAI Platform Engineer - Madrid OR Amsterdam

What you'll will be doing:

As a GenAI Platform Engineer, you will help build and scale the platform capabilities that enable teams across the company to develop, deploy, and operate LLM-powered applications, agents, and MCP-based integrations.

The team focuses on making it easier for engineers to build reliable GenAI systems in production, with strong foundations around developer experience, infrastructure, observability, security, and scalability. You will work on platform capabilities that can be reused across different teams and business use cases, helping engineers move faster without having to solve the same infrastructure problems repeatedly.

This is a highly technical role at the intersection of platform engineering, distributed systems, and GenAI.

• Develop tooling and infrastructure that improves the developer experience for building, testing, deploying, and operating GenAI systems.
• Design and operate services that handle areas such as model access, tool integration, orchestration, evaluation, observability, and runtime infrastructure.
• Build scalable and reliable infrastructure on Kubernetes.
• Work closely with engineering teams to understand their use cases and turn common requirements into reusable platform capabilities.
• Support technically complex and high-impact use cases, helping teams move from experimentation to production.
• Own projects end to end, from architecture and design through implementation, deployment, and operation.
• Identify areas of the platform that can be simplified, standardized, or made more reliable and scalable.
• Work in a cross-functional and cross-border environment with engineers and teams in locations such as Amsterdam, Madrid, San Francisco, and Bangalore.
• Collaborate closely with other platform, infrastructure, security, and product teams.
• Launch early, iterate often, and use feedback from internal developers to continuously improve the platform.
• Contribute to technical design discussions, code reviews, and engineering standards across the organization.

Who you are

• 4+ years of professional experience in Platform Engineering, DevOps, Data Platform Engineering, MLOps, Backend Engineering, ML Engineering, or a similar role.
• You have hands-on experience on Linux system administration, both in cloud and on-premises environments.
• You have strong engineering skills, including version control, coding best practices, debugging, testing, and production readiness.
• You have hands-on experience building or operating LLM-powered applications, agents, or GenAI platforms in production.
• Strong platform engineering experience with Kubernetes, Helm, Argo CD, and GitOps practices.
• Experience with observability tools such as Prometheus, Grafana, Kibana, or similar.
• You are proficient in Python and comfortable working with backend services and APIs.
• You have experience on DevEx and paving the SDLC for users setting up applications on top of your platform.
• You have a good understanding of LLM application architectures, including concepts such as tool calling, RAG, agent workflows, model gateways, and evaluation.
• You can diagnose and resolve issues related to reliability, latency, scalability, cost, and deployment of GenAI systems.
• You understand the importance of security, access control, data privacy, and governance when building shared AI platform capabilities.
• You have an experimental mindset and are comfortable launching early, learning from usage, and iterating quickly.
• You are a strong team player with good communication skills and can explain technical trade-offs to different audiences.
• You are comfortable collaborating with cross-functional teams and helping define standards and best practices for building and operating GenAI systems.

Desirable additional qualifications:

• You have experience working with MCPs.
• Experience with LLM gateways and model abstraction layers such as LiteLLM, including routing, fallbacks, rate limits, cost controls, and multi-provider setups.
• Experience with LLM observability and evaluation tooling such as Langfuse, including tracing, prompt/version tracking, latency and cost monitoring, and production debugging.
• Experience with high-performance LLM serving frameworks such as vLLM, including GPU-backed inference, batching, throughput optimization, and serving OpenAI-compatible APIs is a plus.

What's next?

Adyen is an equal opportunity employer. We do not discriminate based on race, color, ethnicity, ancestry, national origin, religion, sex, gender, gender identity, gender expression, sexual orientation, age, disability, veteran status, genetic information, marital status or any legally protected status.

All your information will be kept confidential according to EEO guidelines.

This role is based out of either our Madrid or Amsterdam offices. We are an office-first company and value in-person collaboration; we do not offer remote-only roles.