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🧭 Role Summary
We are seeking an experienced AI Solutions Architect / Senior AI Engineer to design, build, and maintain enterprise-grade AI solutions that leverage NLP, Machine Learning, and Generative AI. You will define AI solution architectures, train and operationalize advanced models, implement modern MLOps, and present blueprints to both technical and business stakeholders.
🎯 Key Responsibilities
We'll Propose You
We are seeking an experienced AI Solutions Architect / Senior AI Engineer to design, build, and maintain enterprise-grade AI solutions that leverage NLP, Machine Learning, and Generative AI. You will define AI solution architectures, train and operationalize advanced models, implement modern MLOps, and present blueprints to both technical and business stakeholders.
🎯 Key Responsibilities
- AI Solution Engineering
- Develop and maintain AI applications integrating NLP, ML, and Generative AI.
- Train custom ML/DL models (including transformer-based architectures) using structured and unstructured data.
- Architecture & Design
- Design end-to-end IT architectures for AI solutions, selecting appropriate models, components, and techniques.
- Apply modern AI approaches and enterprise IT architecture practices (scalability, security, observability).
- Present solution blueprints to technical and business audiences, moderate discussions, and collect feedback.
- Data, MDM, and MLOps
- Support best practices for data quality, master/metadata management, lineage, and governance.
- Implement modern MLOps: model/version registries, CI/CD for ML, feature stores, monitoring, retraining pipelines.
- Delivery & Integration
- Independently develop, test, document, and integrate AI/ML components into service-oriented architectures.
- Ensure production readiness: reliability, resilience, performance, security, and compliance.
- Collaboration & Communication
- Work closely with cross-functional teams (data engineers, architects, product owners).
- Translate business needs into AI capabilities and measurable outcomes.
- Programming & AI Stack
- Excellent Python skills and core AI/ML/NLP libraries: pandas, scikit-learn, PyTorch, TensorFlow, Transformers, spaCy, NLTK; experience with OpenAI APIs/SDKs.
- Advanced AI Techniques
- Proven experience with LLMs and generative AI (prompting, fine-tuning, adapters/LoRA, retrieval augmentation).
- ML algorithms and NLP pipelines in production contexts.
- Data & Platforms
- Modern data engineering practices: ETL/ELT pipelines, streaming/batch, metadata/model versioning.
- Database integration: SQL (e.g., Postgres) and NoSQL (e.g., Elasticsearch, MongoDB, Cassandra).
- Cloud & Operations
- Hands-on deployment on AWS and/or Azure (compute, storage, security, networking, managed ML services).
- Software engineering and DevOps: Git workflows, CI/CD, containerization (Docker), orchestration (Kubernetes), observability.
- Architecture & Integration
- Experience integrating AI components within service-oriented and event-driven architectures.
- Ability to produce high-quality design docs, diagrams, and PoCs leading to scalable solutions.
- Ethics, Risk, and Compliance
- Awareness of ethical/legal implications of AI (bias, privacy, IP, model/data governance), ideally in enterprise or public sector environments.
- Experience with vector databases (e.g., FAISS, pgvector, Milvus), feature stores, model registries.
- Knowledge of security for AI systems: data anonymization, secret management, network policies, policy-based access.
- Experience with evaluation frameworks (e.g., RAGAS, prompt eval), guardrails, content filtering, red-teaming.
- Familiarity with infrastructure-as-code (Terraform), workflow orchestration (Airflow, Argo), and serverless.
- Prior work with enterprise architecture tools (e.g., Sparx Enterprise Architect).
- Fluent in English (spoken and written).
- All documentation will be produced in English.
- Tools: MS Teams, IntelliJ, JIRA, Enterprise Architect, GitHub/GitLab, Docker, Kubernetes, model registries.
- Methodologies/Frameworks: Agile, PM2@EC.
- Engineering Practices: Domain-Driven Architecture, Test-Driven Development (TDD), Continuous Integration/Delivery (CI/CD), MLOps.
- Location: onsite Brussels
- Contract Type: freelance or employee
We'll Propose You
- An attractive salary package
- A good work-life balance environment
- The assurance of working in cutting-edge technologies in an entrepreneurial spirit.
- The opportunity to develop your skills thanks to tailor-made training courses according to your needs
- A good job in a friendly place
Key Skills
Ranked by relevance
ai
mlops
cicd
kubernetes
docker
containerization
machine learning
elasticsearch
serverless
tensorflow
terraform
cassandra
storage
pytorch
python
devops
pandas
nosql
jira
git
tdd
sql
aws
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- Posted
- Nov 20, 2025
- Type
- Full-time
- Level
- Mid-Senior
- Location
- Brussels
- Company
- Cronos Europa
Industries
Professional Services
Categories
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