Job Description

AI Engineer

Context

We are looking for an AI Engineer responsible for designing, building, integrating, and operationalizing AI solutions in production environments.

The role focuses on implementing concrete AI use cases (not defining the AI strategy), working closely with existing systems and development teams.

Key Responsibilities

AI Solution Development

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  Translate business needs into production-ready AI features
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  Build solutions for use cases such as document processing, classification, summarization, information extraction, and intelligent assistants
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  Work with LLMs, generative AI, retrieval-augmented systems (RAG), and open-source frameworks (e.g., Hugging Face, LangChain, LlamaIndex)

System Integration

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  Integrate AI components into existing applications, APIs, and backend systems (mainly .NET-based environments)
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  Ensure secure, maintainable, and well-governed integrations (access control, validation, auditing)

Evaluation & Quality

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  Define and execute evaluation strategies (accuracy, grounding, hallucinations, consistency, bias)
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  Improve prompts, retrieval logic, and output structures based on test results

Production & Monitoring

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  Move AI prototypes into production-ready services
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  Implement CI/CD, versioning, monitoring, logging, and observability (latency, usage, cost, errors)
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  Ensure reliability, performance, and cost control in production

Collaboration

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  Work closely with developers, architects, security, and business stakeholders
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  Document solutions, limitations, and operational considerations
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  Share best practices for responsible AI usage

Required Skills

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  Strong Python (AI services, backend integration, retrieval pipelines)
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  Good knowledge of C# / .NET (API integration, system collaboration)
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  Experience with generative AI and LLM-based applications
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  Knowledge of retrieval-augmented generation (RAG), embeddings, vector databases (nice to have)
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  Experience with APIs, system integration, and SQL/data processing
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  Understanding of AI evaluation, prompt engineering, and structured outputs
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  Familiarity with CI/CD, containerization, and production deployments (nice to have)
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  Awareness of AI governance, bias, explainability, and security considerations
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  Experience with logging/monitoring tools (e.g., OpenTelemetry, Dynatrace is a plus)

Profile

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  Hands-on, pragmatic, and delivery-focused
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  Strong analytical mindset with attention to quality and risks
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  Ownership of technical implementation in assigned use cases
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  Good communication skills in a multidisciplinary environment
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  Proactive in improving AI solution quality and reliability
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  Quick learner in evolving AI technologies

Languages

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  Dutch or French (one required)
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  Understanding of the second national language is a plus

Working Model

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  Hybrid (2 days onsite, 3 days remote per week)

Engagement Type

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  Freelance or employee (via staffing/detachment structure)