AI engineer

GCS Recruitment; Sint-Joost-ten-Node; Presencial; EUR 70.000 - 110.000; Jornada completa

Descripción de la vacante

GCS Recruitment is seeking an experienced AI Engineer to design, develop, deploy, and maintain AI and machine learning solutions that deliver measurable business value. The role combines strong software engineering with practical ML, generative AI, data, and cloud technologies.

The AI Engineer will collaborate with data scientists, engineers, architects, and stakeholders to translate requirements into scalable, production-ready AI systems.

Formación

• Experience designing, developing, deploying and maintaining AI/ML solutions.
• Ability to translate business needs into scalable AI products.
• Practical knowledge of cloud platforms and modern AI toolchains.

Responsabilidades

• Design, develop, and deploy AI/ML solutions for business and operational use cases.
• Develop production-grade AI applications using Python and modern AI/ML frameworks.
• Build and integrate ML models into enterprise data platforms and apps.
• Develop solutions using Generative AI, LLMs, NLP, and RAG where appropriate.
• Design and implement AI-powered services, APIs, and automation workflows.
• Integrate foundation models and AI services into enterprise environments.
• Develop and optimise prompt engineering, model orchestration, and evaluation approaches.
• Design RAG architectures using enterprise data, vector databases, embeddings, and knowledge bases.
• Build data preparation, feature engineering, model training, and inference pipelines.
• Evaluate models for accuracy, reliability, performance, cost, and business impact.
• Implement monitoring, observability, testing, and continuous improvement for AI systems.
• Apply responsible AI principles covering security, privacy, bias, explainability, and appropriate use of AI.
• Collaborate with data engineers and cloud/platform teams to deploy scalable AI workloads.
• Implement CI/CD and MLOps practices for reliable deployment.
• Troubleshoot model, application, data, performance, and integration issues.

Conocimientos

Python

AI/ML frameworks

Generative AI

NLP

RAG

Cloud technologies

CI/CD & MLOps

Model evaluation

Herramientas

Python

Vector databases

LLMs

Descripción del empleo

AI Engineer

Role Overview

We are seeking an experienced AI Engineer to design, develop, deploy, and maintain AI and machine learning solutions that deliver measurable business value. The ideal candidate will combine strong software engineering skills with practical experience in machine learning, generative AI, data, and cloud technologies.

The AI Engineer will work closely with data scientists, data engineers, architects, software engineers, and business stakeholders to translate business requirements into scalable, reliable, and production-ready AI solutions.

Key Responsibilities

• Design, develop, and deploy AI and machine learning solutions for business and operational use cases.
• Develop production-grade AI applications using Python and modern AI/ML frameworks.
• Build and integrate machine learning models into enterprise applications and data platforms.
• Develop solutions using Generative AI, Large Language Models (LLMs), Natural Language Processing (NLP), and Retrieval-Augmented Generation (RAG) where appropriate.
• Design and implement AI-powered applications, services, APIs, and automation workflows.
• Integrate foundation models and AI services into enterprise technology environments.
• Develop and optimise prompt engineering, model orchestration, and evaluation approaches.
• Design and implement RAG architectures using enterprise data, vector databases, embeddings, and knowledge bases.
• Build data preparation, feature engineering, model training, and inference pipelines.
• Evaluate models and AI solutions for accuracy, reliability, performance, cost, and business effectiveness.
• Implement monitoring, observability, testing, and continuous improvement for AI systems.
• Apply responsible AI principles covering security, privacy, bias, explainability, and appropriate use of AI.
• Work with data engineering teams to ensure AI solutions have reliable and appropriately governed data.
• Collaborate with cloud and platform engineering teams to deploy scalable AI workloads.
• Implement CI/CD and MLOps practices to support repeatable and reliable model deployment.
• Troubleshoot model, application, data, performance, and integration issues.
• Keep up to date with developments in AI, machine