Artificial Intelligence Engineer

Harvey Nash; Brussel Hoofdstad; Sur place; EUR 55 000 - 90 000; Plein temps

Résumé du poste

Harvey Nash is seeking a Medior AI Engineer to design, develop and deploy AI solutions, focusing on Generative AI, LLMs, and RAG. You will work with data scientists, engineers and business experts to deliver production-ready applications.

You will translate business needs into scalable AI products, apply DevOps and MLOps practices, and communicate complex concepts to technical and non-technical stakeholders.

Qualifications

• Master's degree in Artificial Intelligence, Computer Science, Engineering, Data Science or a related technical field
• 2+ years of experience in AI/ML engineering, including experience contributing to the development and deployment of AI solutions in production environment

Responsabilités

• Develop AI and Generative AI applications using modern technologies and frameworks
• Translate business requirements into practical AI solutions
• Develop LLM-based applications and RAG solutions
• Contribute to the design and implementation of Agentic AI workflows
• Prototype, test and validate AI solutions with business stakeholders
• Deploy, monitor and maintain AI applications in production
• Apply software engineering, DevOps and MLOps best practices
• Communicate results and technical concepts to both technical and non-technical audiences
• Contribute to knowledge sharing and continuous improvement within the team

Connaissances

Python

AI & Generative

LLM frameworks LangChain

LlamaIndex

Agentic AI

RAG solutions

Prompt engineering

LLM evaluation

Azure cloud

Git/GitHub

CI/CD pipelines

MLOps

Communication skills

Formation

Master's degree in AI/CS/Engineering/Data Science

Outils

Azure

MLflow

GitHub Actions

DevOps tools

LangChain

Description du poste

As a Medior AI Engineer, you will contribute to the design, development and deployment of AI solutions that support business needs. You will work with Generative AI technologies, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), cloud platforms and modern software engineering practices to build scalable and impactful solutions.

Working closely with business experts, data scientists, data engineers and fellow AI engineers, you will help transform innovative ideas into production-ready applications while continuously learning and growing your expertise in AI.

Responsibilities

• Develop AI and Generative AI applications using modern technologies and frameworks
• .Translate business requirements into practical AI solutions
• .Develop LLM-based applications and RAG solutions
• .Contribute to the design and implementation of Agentic AI workflows
• .Prototype, test and validate AI solutions with business stakeholders
• .Deploy, monitor and maintain AI applications in production
• .Apply software engineering, DevOps and MLOps best practices
• .Communicate results and technical concepts to both technical and non-technical audiences
• .Contribute to knowledge sharing and continuous improvement within the team

Profile

• Master's degree in Artificial Intelligence, Computer Science, Engineering, Data Science or a related technical field
• .2+ years of experience in AI/ML engineering, including experience contributing to the development and deployment of AI solutions in production environment

Technical Skill

s AI & Generative

• AIStrong expertise in Pytho
• n.Strong knowledge of AI, Machine Learning and Generative AI concept
• s.Experience with LLM frameworks such as LangChain or LlamaInde
• x.Experience with Agentic AI frameworks such as LangGraph, AutoGen or CrewA
• I.Experience designing and implementing Retrieval-Augmented Generation (RAG) solution
• s.Understanding of prompt engineering and LLM evaluatio

Software Engineering, DevOps & MLO

• ps Experience with at least one major cloud platform (Azure preferre
• d).Strong knowledge of Git and GitH
• ub.Experience with CI/CD pipelines and DevOps practices is a pl
• us.Experience deploying and maintaining applications in cloud environments is a pl
• us.Experience with Azure DevOps, GitHub Actions or similar tools is a pl
• us.Familiarity with MLOps concepts and tools such as MLflow is a pl
• urs Excellent problem-solving ski
• lls.Collaboration: Strong interpersonal skills to work effectively with diverse stakeholders from data science, engineering, and business un
• its.Excellence: Strong commitment to excellence by consistently striving for high-quality outcomes, embracing continuous improvement, and maintaining a proactive, detail-oriented approach in all ta
• sks.Innovation Mindset: Willingness to explore new technologies and methodologies to drive continuous improvem
• ent.Resilience: Capacity to troubleshoot and resolve issues in complex changing environments while maintaining a focus on quality and user experie
• nce.Communication: Ability to convey complex technical concepts to non-technical audiences and provide clear documentat