AI Engineer
Role details
Job location
Tech stack
Job description
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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.
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Generative AI & LLMs: Develop AI assistants, copilots, intelligent agents, and RAG applications. Implement prompt engineering, orchestration, and optimization strategies to maximize business value.
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AI Architecture & Engineering: Design scalable APIs, microservices, and cloud-native AI architectures. Implement vector search, semantic search, and knowledge retrieval solutions.
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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.
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MLOps & LLMOps: Implement automated deployment, monitoring, governance, and lifecycle management processes for AI solutions, following MLOps and LLMOps best practices.
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Data Engineering & AI Enablement: Develop data pipelines and feature-engineering processes that support AI and analytics workloads while ensuring data quality and scalability.
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Client Interaction: Work closely with clients to translate business requirements into AI solutions and present concepts, prototypes, and results to diverse stakeholders.
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Collaboration: Collaborate with data engineers, software developers, AI specialists, cybersecurity experts, and project managers to deliver end-to-end solutions.
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Continuous Innovation: Stay up to date with emerging AI technologies and contribute to innovation and knowledge sharing across the organization.
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Een functie waarin je actief bijdraagt aan de verdere ontwikkeling en groei van de AI & Digital-divisie binnen TÜV Austria, met impact op innovatieve projecten rond Artificial Intelligence, Generative AI en Agentic AI in uiteenlopende sectoren.
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Een ondersteunende en collegiale werkomgeving met een open en respectvolle bedrijfscultuur, waar kennisdeling, samenwerking en continue verbetering centraal staan.
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De kans om te werken met de nieuwste AI-technologieën, cloudplatformen en enterprise-oplossingen, en organisaties te ondersteunen bij het creëren van waarde met moderne AI-capaciteiten.
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Een organisatie die haar winst bewust herinvesteert in medewerkers, technologie en dienstverlening, zodat je werkt in een omgeving die voortdurend innoveert en inspeelt op nieuwe technologische ontwikkelingen.
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Uitgebreide mogelijkheden voor professionele ontwikkeling via opleidingen, certificeringen en praktijkervaring binnen Artificial Intelligence, Generative AI, Machine Learning, Cloud AI Services, MLOps en AI Engineering.
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De mogelijkheid om een sleutelrol te spelen in het vormgeven van de toekomst van AI-gedreven dienstverlening en digitale innovatie binnen TÜV Austria Belgium en haar klanten.
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Flexibele werkregelingen en een gezonde work-life balance, zodat je zowel professioneel als persoonlijk optimaal kunt presteren.
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Een competitief salarispakket aangevuld met een uitgebreid pakket extralegale voordelen, waaronder:
- Maaltijdcheques van €8 per gewerkte dag en ecocheques ter waarde van €250 per jaar.
- Hospitalisatieverzekering (inclusief ambulante zorgen en tandzorg), groepsverzekering en de mogelijkheid om gezinsleden aan te sluiten.
- Eindejaarspremie.
- Mobiel abonnement en een Bring Your Own Device-vergoeding.
- Laptop.
- Bedrijfswagen met laadkaart of mobiliteitsbudget.
- Flexibel Inkomensplan (FIP) met mogelijkheden zoals extra vakantiedagen, aankoop van telecomtoestellen, fietsleasing, enzovoort.
- Anciënniteitsverlof vanaf 2 jaar dienst.
- Glijdende werktijden, telewerkmogelijkheden en aandacht voor een gezonde work-life balance., * Commitment to responsible AI, data privacy, security, governance, and compliance with relevant regulations and industry standards.
Requirements
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related field., * 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 and is required.
Technical Skills:
- Strong proficiency in Python; experience with Java, C#, or JavaScript is considered an asset.
- 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.
- Machine Learning & AI:
- 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.
- Cloud Platforms & AI Services:
- Microsoft Azure: Azure OpenAI, Azure AI Foundry, Azure Machine Learning, Azure AI Search, Microsoft Fabric.
- 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.
Benefits & conditions
Pulled from the full job description
- Retirement plan
- Additional leave
- Company car
- Food allowance
- Hospitalization insurance
- Eco vouchers