Artificial Intelligence Engineer

Harvey Nash; Belgique; Sur place; EUR 60 000 - 90 000; Plein temps

Résumé du poste

Harvey Nash is seeking a Medior AI Engineer to contribute to designing and deploying AI solutions that support business needs. You will work with Generative AI, LLMs, and RAG on cloud platforms, applying modern software engineering practices to build scalable applications.

You will collaborate with business experts, data scientists and engineers to translate ideas into production-ready solutions while growing your expertise in AI and staying current with industry trends.

Qualifications

• Master's degree in AI/CS/Engineering/Data Science or related field.
• 2+ years of AI/ML engineering experience with production deployments.

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.
• Prototype, test and validate AI solutions with stakeholders.
• Deploy, monitor and maintain AI applications in production.
• Apply software engineering, DevOps and MLOps best practices.

Connaissances

Python

AI/ML

LangChain

LlamaIndex

LangGraph

AutoGen

CrewAI

RAG

Prompt engineering

LLM evaluation

Azure

Git

GitHub Actions

CI/CD

MLOps

Cloud platforms

Collaboration

Communication

Formation

Master's degree in Artificial Intelligence, Computer Science, Engineering, Data Science or a related technical field

Outils

Azure

MLflow

GitHub Actions

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

s 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

n. 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

us. Attitudes & Behavio

• urs Excellent problem-solving ski
• lls.Collaboration: Strong interpersonal skills to work effectively for 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

ion. Langu

• ages Fluent in Eng
• lish.French and/or Dutch is a strong a