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Applied AI Engineer

About the Role

A leading frontier AI company is looking for an Applied AI Engineer to join their Solutions team in Munich.

This is a customer-facing technical role, but the balance is heavily technical: roughly 20% involves presales support, onboarding, and client guidance - the other 80% is designing, developing, and deploying AI solutions for B2B enterprise clients.

Your stakeholders are technical. You won't be simplifying things for non-technical audiences - you'll be working directly with data scientists, software engineers, and CTOs on complex, high-impact implementations.

This is not a consultancy role. You'll operate with the mindset of a startup CTO embedded in a world-class AI team: owning projects end-to-end, shipping working solutions, and collaborating closely with researchers and product engineers on the company's most challenging customer problems.

What You'll Do

Deploy AI solutions into production across various industries, delivering measurable business impact
Build state-of-the-art GenAI applications - from consumer products to industrial use cases
Develop complex implementations involving fine-tuning, advanced RAG pipelines, agentic workflows, and custom LLM applications
Participate in presales calls to understand client needs and provide technical guidance
Collaborate with researchers and product engineers on the team's most demanding customer projects
Feed customer insights back into product and model development

How the Team Works

What matters is what you ship, not the time you spend on it
No bureaucracy - you talk to whoever you need to, the best idea wins
Low ego, high standards; direct, honest feedback
Unstructured environment where people find joy in ambiguity

About You

Fluent in English and German (required for this Munich-based role)
2+ years as a technical individual contributor (data scientist or software engineer) on AI-based products
Proven experience implementing AI/ML products with APIs, back-end and front-end interfaces
Hands-on experience with fine-tuning LLMs, advanced RAG, or agentic use cases
Deep understanding of machine learning concepts and the algorithms underlying LLMs
Strong Python coding skills
Able to explain complex technical concepts clearly to technical audiences

Nice to Have

Open-source contributions, especially in the LLM space
Prior experience as a Customer Engineer, Forward Deployed Engineer, Solutions Architect, or Technical PM
Experience with PyTorch and deep learning

Compensation