AI LLM Engineer – Remote-First

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What's in it for you

We are currently on the lookout for an AI LLM Engineer with strong hands-on expertise in large language models and retrieval-augmented generation. You will be a key member of the team, responsible for evaluating cutting-edge generative AI tools, designing and benchmarking RAG systems, and experimenting with advanced prompting techniques. 

Beyond building pipelines, you will play a central role in shaping how we ground AI outputs in factual, reliable data, ensuring our solutions are not only powerful but also trustworthy and user-friendly.

About the team

You'll join a pan-European AI team directly reporting to the CTPO of the company. The team is dedicated to building reliable and impactful GenAI solutions and operates in an Agile environment and works closely across countries to design, benchmark, and deploy LLM and RAG systems that truly make a difference. They are located across Europe, in Germany, France, the Netherlands and Belgium.

Your impact

• Evaluate and benchmark LLMs and RAG systems using metrics such as accuracy, relevance, latency, and hallucination rate
• Test and compare LLM-based tools across tasks like summarization, code generation, and Q&A
• Design and implement end-to-end RAG pipelines, selecting appropriate models, vector stores, and retrieval strategies
• Build and optimize semantic search and embedding workflows to ensure scalable, low-latency retrieval
• Experiment with prompting strategies (few-shot, chain-of-thought, role-based) to improve coherence and factuality
• Collaborate with cross-functional teams to integrate GenAI solutions into workflows and enhance user experience
• Stay ahead of trends in LLMs, RAG, and GenAI agents by testing emerging libraries, APIs, and platforms

Technology stack

• Languages & frameworks: Python, PySpark, Numpy, Pandas, TensorFlow
  
• RAG frameworks: LangChain, LlamaIndex, Haystack, Guidance, PromptLayer
  
• LLM & GenAI platforms: Hugging Face Transformers, OpenAI API, Anthropic Claude, Mistral
  
• Generative AI tools: Microsoft Copilot, GitHub Copilot, Atlassian Rovo
• Infrastructure & deployment: AWS, Docker, Kubernetes

To succeed, you should meet at least 70% of these requirements

• 3 to 5 years experience working as a AI Engineer with 2 to 3 years experience on  LLM-based applications, including RAG systems in real-world use cases  
• Strong understanding of how GenAI agents for information retrieval work 
• Ability to design and apply evaluation metrics for LLM performance (accuracy, relevance, hallucination rate, latency)
• Hands-on experience with RAG frameworks such as LangChain, LlamaIndex, or Haystack  
• Fluent in English (CEFR C1 or C2) is mandatory; proficiency in German, Dutch, French, or any additional European languages is a plus

If this looks like you, the recruitment steps are:

1. A first call with one of our recruiters
2. An interview focused on the mission and your expertise with your future manager
3. A final interview with on of CPTO 
4. Hopefully, an offer you can't refuse

Turn back if …

• You've used LLMs or GenAI tools in the past, but never looked under the hood
• You expect fully predefined processes and frameworks instead of experimenting and iterating in ambiguous situations
• You have never heard of LLM grounding issues and how to solve them.
• You prefer working only with out-of-the-box solutions rather than designing and fine-tuning your own
  

Otherwise apply

Our commitment to equal employment opportunities

EPI offers the same job opportunities to all, without distinction of gender, ethnicity, religion, sexual orientation, social status, disability or age. EPI promotes the development of an inclusive work environment that mirrors the diversity of the clients our product is serving.