AI Platform Engineer (m/f/d)

Role Overview

This is how we work – please read carefully

This position is not for everyone, and that’s intentional. To help you assess if it’s a good fit for you:

• You build the rails, not just the trains. While other roles in AI work on specific use cases, you are responsible for the end-to-end aspects: infrastructure, frameworks, reusable components, guardrails. Your work pays off by enabling others to deliver solutions faster and more safely.
• Efficiency is your constant companion. AI resource consumption – tokens, compute, API costs – grows quickly and invisibly. You keep it in check, make informed decisions about build vs. buy (on-prem vs. cloud, build vs. buy), and can justify them.
• You will say “no” more often than “yes”. Not every brilliant idea needs its own infrastructure, and not every model needs to be hosted independently. You understand when the pragmatic path is the best and advocate for it, even against enthusiastic colleagues.
• Every team member acts very autonomously. You set your own standards and critically review your results before anyone else does. Exchange and feedback are, of course, welcome, but quality control of your work starts with you.
• You are the specialist in your domain. Our team is intentionally interdisciplinary, with minimal overlap between disciplines. You have specialists for frontend, backend, UX, and AI applications, but platform, operations, and efficiency are your domain, and you own them with expertise.
• We develop consistently with AI support. Tools like Claude Code or Cursor are standard practice here, not an experiment. This shifts the focus of work: less manual coding, more architectural definition and critical evaluation of results. You don’t have to write every line yourself, but you are responsible for every line you deliver.
• Weekly free time slots are scheduled – around 10% of your working time. Time for professional development, personal ideas, and creative exchange is part of the working week – not a nice-to-have that disappears into the daily grind.
• Result-oriented and process-lean. We need fast, pragmatic solutions that work in daily life, not 100% systems refined over months. The platform grows with real needs, not theoretical ones.

If you are most productive when given a ready-made architecture and a defined backlog, you won't be happy with us. If you are drawn to creating a foundation from scratch that others can build upon – then read on.

Our Stack

We primarily work with C# / .NET, close to the product. We use Python where it makes sense – for prototypes, tools, AI-specific tasks, data work, and tooling. However, the main focus is on C#. We build our frontends with React – this is not mandatory for this role, but beneficial. For AI operations and infrastructure, we expect familiarity with common inference and orchestration frameworks, as well as containerization.

Your Tasks

• Design, build, and operate the technical platform for our AI applications: model hosting, inference, API gateways/routing, reusable components.
• Evaluate, configure, and operate on-premise / self-hosted LLMs – including quantization, GPU sizing, and performance.
• Ensure transparency of AI resource consumption and costs, actively manage them; make and justify informed build/buy and on-prem/cloud decisions.
• Select and implement frameworks, tools, and standards for the team – guardrails that make AI development faster and safer.
• Transform successful prototypes from other AI roles into a viable, operational state – all the way to handover for R&D or production deployment.
• Own CI/CD, monitoring, and operational aspects of AI solutions.
• Present results and recommendations to product and business teams – at the appropriate technical level for your counterpart.

Your Profile

• Deep understanding and practical experience operating AI/LLM applications in an enterprise environment: inference frameworks (e.g., vLLM, Ollama, llama.cpp, TGI), API gateways/routing (e.g., LiteLLM), RAG and embedding infrastructure.
• Operational experience with on-premise models / self-hosted LLMs in an enterprise context – including quantization and resource sizing.
• Many years of deep, hands-on experience developing software solutions in an enterprise environment, with a significant portion involving C# / .NET – demonstrating clear technical depth.
• Experience with containerization (Docker), CI/CD, and operational aspects.
• Strong awareness of costs and efficiency – you can measure, assess, and optimize AI resource consumption.
• Good understanding of current trends, available off-the-shelf solutions, and new developments in AI – you know when to build and when to buy.
• Very good German language skills (the team's language is German) and good English language skills.
• Primarily remote work, with willingness for occasional travel to our headquarters in Landau (approx. 5-10% of working time).

Must-Haves

• Hands-on experience in an enterprise environment with on-premise models / self-hosted LLMs – including quantization and resource sizing.
• Hands-on experience in an enterprise environment operating AI/LLM applications: inference frameworks (e.g., vLLM, Ollama, llama.cpp, TGI), API gateways/routing (e.g., LiteLLM), RAG and embedding infrastructure.
• Experience with containerization (Docker), CI/CD, and operational aspects.
• You can say "no" without closing doors and admit failures, even if you've already invested effort.

Nice-to-Haves

• Experience in expert leadership or mentoring developers.
• Good Python skills for tooling and prototyping.
• Experience with data preparation and pipelines (ETL/ELT).
• React / modern web frontends.
• Experience with GPU infrastructure and cost optimization in a cloud environment.

Does this sound like you?

• You think systemically and foundationally, not just in terms of individual solutions – and build so others can rely on it.
• You have a good sense of proportion – you build infrastructure that fits the problem, not the biggest possible. And you understand when the pragmatic path is the right one.
• You can say "no" without closing doors and admit failures, even if you've already invested effort.
• You critically review your own results before anyone else does.
• An open eye for shortcomings and potential, both technical and organizational.

Reasons to become part of AMDT

• Transformational Opportunities & Integrative Culture: Join a dynamic, evolving company where growth is encouraged, your contributions are valued, and you can collaborate and thrive within a diverse, supportive community.
• Flexible Work Arrangements: Work in a way that suits you best – remotely, hybrid, or in our modern office space.
• Future-Proofing Your Career: We invest in your future with a 20% contribution towards a comprehensive company pension plan.
• Enhanced Health Coverage: Enjoy added security with supplementary health insurance that supports your well-being beyond the standard coverage.
• Corporate Perks: Benefit from exclusive discounts on select brands, enriching your everyday life.
• Continuous Learning: Utilize Preply to effortlessly learn languages, supporting your personal and professional development.
• Milestone Celebrations: Be celebrated with gifts for significant life events like weddings, the arrival of a child, or your company anniversary.

Get in Touch

Should you have any questions regarding this vacancy, please reach out to our recruiting team (Chiara & Dirk) at recruiter contact, referencing the job title.