AI Engineer

TÜV AUSTRIA BELGIUM NV/SA; Rotselaar; Sur place; EUR 90 000 - 140 000; Plein temps

Avantages offerts par ce poste

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Résumé du poste

TÜV AUSTRIA BELGIUM NV/SA is seeking an experienced AI Engineer to strengthen our Data Intelligence team in Belgium. You will design, develop, and deploy AI solutions, working with Generative AI, LLMs, and cloud-native architectures across Azure, AWS, and Google Cloud.

The role emphasizes end-to-end AI pipelines, MLOps, and customer collaboration. Requirements include 5+ years in AI engineering, fluency in Dutch and English, and a strong background in building production-grade AI systems.

Qualifications

• Minimum 5 years of experience in AI engineering, ML, software development, or data engineering.
• Fluency in Dutch and English (written and spoken) is required.
• Experience delivering AI solutions from concept to production deployment.
• Experience working directly with customers to translate requirements into scalable technical solutions.

Responsabilités

• AI Solution Development: design, develop, and deploy end-to-end AI applications.
• Generative AI & LLMs: build assistants, copilots, and RAG solutions; implement prompt engineering.
• AI Architecture & Engineering: design scalable APIs, microservices, and cloud-native architectures.
• Cloud AI Platforms: deploy on Azure, AWS, Google Cloud using respective AI services.
• MLOps & LLMOps: automate deployment, monitoring, governance, lifecycle management.
• Data Engineering & AI Enablement: develop data pipelines and feature engineering for AI workloads.
• Client Interaction: translate business needs into AI solutions and present results.
• Collaboration: work with data engineers, software developers, cybersecurity, project managers.
• Continuous Innovation: stay updated with AI tech and contribute knowledge sharing.

Connaissances

Generative AI

LLMs

MLOps

Cloud platforms

Data engineering

API design

Microservices

DevOps

Docker

Kubernetes

Formation

Bachelors or Masters in Computer Science or related

Outils

LangChain

LlamaIndex

Semantic Kernel

Vector databases

Description du poste

Experience Level: five to ten years of experience

Job Status: Employee

What will you do?

TÜV Austria Belgium is looking for a highly qualified and motivated AI Engineer to strengthen our Data Intelligence team. In this role, you design, develop, and deploy innovative AI solutions that help organizations solve complex business challenges and unlock value from data. You work with machine learning, Generative AI, and cloud technologies to build scalable, production-ready applications.

Are you passionate about Artificial Intelligence, Large Language Models, and cloud-native architectures? Then we look forward to receiving your application.

Key Responsibilities

AI Solution Development: Design, develop, and deploy AI and machine learning solutions. Build end-to-end AI applications, from data ingestion and model development to deployment and monitoring.

Generative AI & LLMs: Develop AI assistants, copilots, intelligent agents, and RAG applications. Implement prompt engineering, orchestration, and optimization strategies to maximize business value.

AI Architecture & Engineering: Design scalable APIs, microservices, and cloud-native AI architectures. Implement vector search, semantic search, and knowledge retrieval solutions.

Cloud AI Platforms: Build and deploy AI solutions on Microsoft Azure, AWS, and Google Cloud, leveraging platforms such as Azure OpenAI, Azure AI Foundry, AWS Bedrock, SageMaker, and Vertex AI.

MLOps & LLMOps: Implement automated deployment, monitoring, governance, and lifecycle management processes for AI solutions, following MLOps and LLMOps best practices.

Data Engineering & AI Enablement: Develop data pipelines and feature-engineering processes that support AI and analytics workloads while ensuring data quality and scalability.

Client Interaction: Work closely with clients to translate business requirements into AI solutions and present concepts, prototypes, and results to diverse stakeholders.

Collaboration: Collaborate with data engineers, software developers, AI specialists, cybersecurity experts, and project managers to deliver end-to-end solutions.

Continuous Innovation: Stay up to date with emerging AI technologies and contribute to innovation and knowledge sharing across the organization.

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Who are you?

Education:

Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related field.

Experience:

Minimum 5 years of experience in AI engineering, machine learning, software development, or data engineering.

Proven track record of delivering AI solutions from concept and prototyping through production deployment.

Experience working directly with customers and translating business requirements into scalable technical solutions.

Fluency in both written and spoken Dutch and English is required.

Technical Skills:

Generative AI & LLMs:

Hands-on experience building Generative AI applications leveraging Large Language Models (LLMs) and foundation models.

Experience with frameworks and libraries such as LangChain, LlamaIndex, Semantic Kernel, or similar technologies.

Familiarity with Retrieval-Augmented Generation (RAG), vector databases, semantic search, knowledge retrieval, and AI agent frameworks.

Experience integrating AI coding assistants and autonomous agent capabilities into software engineering workflows.

Experience with machine learning and deep learning frameworks such as PyTorch, TensorFlow, Scikit-learn, or equivalent technologies.

Understanding of model evaluation, prompt engineering, fine-tuning, and responsible AI practices.

AWS: Bedrock, SageMaker, Lambda, and related AI/ML services.

Google Cloud: Vertex AI and associated machine learning services.

Software Engineering & Architecture:

Experience designing and developing APIs, microservices, and modern cloud-native applications.

Strong understanding of software architecture patterns and scalable application design.

Experience with Git-based development workflows and modern software engineering best practices.

DevOps, MLOps & LLMOps:

Experience with DevOps, MLOps, and LLMOps methodologies.

Familiarity with CI/CD pipelines, automated testing, model monitoring, and AI application lifecycle management.

Experience with containerization and orchestration technologies such as Docker and Kubernetes.

Analytical Thinking:

Ability to analyze complex business challenges and design innovative AI-driven solutions that deliver measurable business value.

Communication:

Strong communication and stakeholder management skills, with the ability to explain complex AI concepts to both technical and non-technical audiences.

Ethical Standards:

Commitment to responsible AI, data privacy, security governance, and compliance with relevant regulations and industry standards.