Expleo Group AI Engineer interview questions & guide 2026

The following questions are representative of the patterns observed in Expleo Group hiring loops. While the exact questions may vary based on your specific team and seniority, focus on mastering the underlying concepts and demonstrating your thought process.

Generative AI & NLP

Focuses on your ability to work with modern transformer architectures and generative workflows.

• How do you design and optimize a RAG pipeline to minimize hallucinations?
• What are the primary trade-offs between fine-tuning an LLM versus using prompt engineering with a vector database?

Preparation at Expleo Group requires a balance of theoretical knowledge and practical, hands-on experience. You should be able to articulate not just how a model works, but why you chose a specific architecture over another in a production context.

Technical Depth – Your interviewers will probe the mathematical and architectural foundations of your projects. Be prepared to defend your design choices, including the trade-offs between accuracy, latency, and cost.

Problem-Solving Structure – When faced with a system design scenario, do not jump straight to the solution. Clearly define the SLOs (Service Level Objectives), identify the bottlenecks, and propose a modular, scalable architecture.

Communication & Translation – A key part of the AI Engineer role is explaining technical outcomes to business teams. Practice summarizing complex technical results into clear, actionable business recommendations.

Cultural Alignment – Expleo Group values candidates who are proactive, collaborative, and capable of working within a structured industrial environment. Demonstrate your ability to work within established processes while still advocating for innovation.

The recruitment process at Expleo Group is designed to be efficient and focused. It typically begins with an initial screening to assess your background and motivation, followed by a deeper technical evaluation. You should expect a rigorous discussion where you will be asked to walk through your previous experiences in detail, often referring directly to your CV.

The process is highly collaborative, involving interactions with both hiring managers and technical leads. The pace is generally steady, with a focus on evaluating your practical ability to contribute to ongoing industrial projects rather than just theoretical knowledge.

This timeline illustrates the progression from initial screening to technical deep dives. Use this to structure your preparation, ensuring you have enough time to review your past projects (as these are key topics) while also brushing up on your system design fundamentals.

LLM Implementation & RAG

This area is critical given the current focus on generative AI. You must be comfortable with the entire stack, from vector databases to evaluation frameworks.

Be ready to go over:

• RAG Architecture – Understanding retrieval, augmentation, and generation components.
• Vector Search – Experience with tools like FAISS, Pinecone, or Milvus.

As an AI Engineer, your primary objective is to bridge the gap between raw data and industrial application. You will spend a significant portion of your time identifying business problems that can be solved with AI, translating these into mathematical frameworks, and developing high-performance models.

Collaboration is central to the role. You will work closely with engineering teams to industrialize your models, ensuring they fit seamlessly into existing software architectures. You are also responsible for the continuous monitoring and improvement of these models, which includes analyzing performance metrics and iterating on training data or architecture based on real-world feedback.

A strong candidate for the AI Engineer position at Expleo Group brings a blend of advanced technical expertise and practical engineering experience.

• Must-have skills: 5+ years of experience in AI or Data Science, proficiency in Python, and strong knowledge of Machine Learning and Deep Learning frameworks. You must also have experience with SQL, NoSQL, and cloud-based infrastructure.
• Nice-to-have skills: Familiarity with CI/CD tools, Big Data technologies, and experience in industrializing AI solutions.
• Soft skills: Strong communication skills to explain complex solutions to non-experts and a high degree of autonomy in managing project lifecycles.

Q: How much time should I spend preparing? A: Dedicate at least 2–3 weeks to review your past projects and practice system design scenarios. The depth of the technical questions requires a solid grasp of both theory and implementation.

Q: Is there a heavy focus on coding? A: Yes, expect a mix of algorithmic challenges and practical coding tasks related to data manipulation or model implementation.

Q: What is the culture like at Expleo Group? A: The culture is professional and project-driven. You will work in an environment that values technical excellence and the ability to deliver results in a structured, industrial context.

Q: How long does the process usually take? A: The process is typically efficient, often moving from the initial screen to a final offer within a few weeks, depending on the speed of the hiring team.

• Own your CV: Every line on your CV is fair game. Be prepared to explain the "why" and "how" for every project listed.
• Focus on Trade-offs: In system design, there is rarely one "right" answer. Always articulate the pros and cons of your chosen approach.
• Use the STAR Method: For behavioral questions, use the Situation, Task, Action, and Result framework to keep your answers concise and impactful.
• Be Business-Minded: Always connect your technical solutions back to the business problem. Explain why your solution is the most cost-effective or efficient for the client.

The AI Engineer role at Expleo Group offers a unique opportunity to apply advanced AI techniques to high-impact industrial problems. By focusing your preparation on RAG pipelines, system design for LLM serving, and the ability to articulate your past technical decisions, you will be well-positioned to succeed in your interviews. Remember that this role values the ability to bridge the gap between research and production.

You can explore additional interview insights, practice questions, and preparation resources on Dataford. Stay confident, focus on your technical strengths, and demonstrate your passion for solving real-world challenges.

The compensation module above provides the current salary range for this role. Use this as a benchmark to understand the market value for an AI Engineer at Expleo Group, noting that actual offers are typically tailored based on your years of experience, specialized expertise, and the specific location of the position.