IT Architect Generative AI (Senior)

Rhox; Brussel; Sur place; EUR 90 000 - 140 000; Plein temps

Résumé du poste

Rhox is seeking an AI Architect to define reference architectures and guide the industrialisation of generative AI and ML solutions. You will design architectures for LLMs, AI agents, and computer vision, and shape a controlled environment for developing, testing, validating and operating AI applications.

You will lead technical decisions on cloud, hybrid and on-premise solutions, data platforms, and microservices, collaborating with project managers and cross-functional teams.

Qualifications

• At least five years designing and developing software solutions, including AI/ML architecture.
• Proven experience designing, industrialising and deploying AI solutions in production.

Responsabilités

• Define reference AI architectures across the organisation.
• Design architectures for LLMs, generative AI, RAG, AI agents, CV and Speech AI.
• Shape controlled environment for developing, testing, validating and operating AI applications.
• Guide cloud, hybrid and on-premise architectures, data platforms, APIs, event-driven systems, containers and Kubernetes.
• Establish AI Engineering and MLOps practices, alongside DevSecOps and AI Governance.
• Assess feasibility and risks with project managers, aligning with IT strategy.

Connaissances

AI Architecting

MLOps

Cloud & Hybrid

REST APIs

Docker

Kubernetes

Python

Security & Compliance

Data Protection

Regulatory Alignment

Stakeholder Communication

Technical Leadership

Formation

Master’s degree in CS/AI or related field

Outils

Docker

Kubernetes

Azure

MLflow

REST APIs

Description du poste

A federal public service is building a responsible approach to artificial intelligence, with a controlled environment for developing, testing and validating applications before operational use. The multidisciplinary team needs an AI architect to define reference architectures and guide the industrialisation of generative AI and machine learning solutions.

The mission

AI initiatives must combine experimentation with security, governance, data protection and compliance, including requirements arising from the AI Act. The controlled environment allows teams to gain experience, manage risks and validate solutions before wider operational use. This approach gives staff safe, legal and ethical access to AI for operational and support tasks.

As the technical reference for AI architecture, you translate operational needs into maintainable solutions that fit a complex existing IT ecosystem. Your scope covers generative AI, Large Language Models, Machine Learning and Deep Learning, from feasibility and architecture choices through MLOps, production deployment and operational use. You work with project managers, operational partners and technical teams, providing technical leadership without direct line management. You also contribute to the design and evolution of the environment used to develop, experiment with and operate AI solutions.

Your responsibilities

• Define and evolve reference architectures for AI across the organisation.
• Design architectures for LLMs, generative AI, RAG, AI agents, computer vision and Speech AI.
• Shape a controlled environment for developing, testing, validating and operating AI applications.
• Guide cloud, hybrid and on-premise architectures, data platforms, APIs, event-driven systems, containers and Kubernetes.
• Establish AI Engineering and MLOps practices, alongside DevSecOps and AI Governance.
• Assess feasibility and risks with project managers, aligning solutions with the wider IT strategy.
• Evaluate emerging AI technologies and recommend those with clear operational value.

Your profile

Essential skills

• At least five years designing and developing software solutions, including at least two years architecting AI or Machine Learning solutions.
• Proven experience designing, industrialising and deploying AI solutions in production, from requirements analysis through operational use.
• Strong knowledge of modern AI, including LLMs, generative AI, RAG, AI agents, Machine Learning, Deep Learning and NLP.
• Understanding of AI Engineering and MLOps across CI/CD, model monitoring, versioning, retraining and MLflow.
• Experience with cloud and hybrid architectures, Microsoft Azure and Azure AI Services, plus integration within complex IT environments.
• Strong software architecture skills with REST APIs, microservices, distributed and event-driven architectures.
• Experience with Docker and Kubernetes for containerisation and orchestration.
• Experience using SQL, NoSQL and vector databases.
• Python development experience.
• Ability to integrate cybersecurity, data protection, traceability, auditability, model risk management and regulatory compliance into architecture.
• Ability to analyse complex needs, compare scenarios and propose practical trade-offs.
• Ability to explain complex technical concepts, advise decision-makers and align multidisciplinary stakeholders.
• Technical leadership skills for guiding teams without direct line management.

Languages

• English, B2
• French, B2
• Dutch, B2

Education

• Master’s degree or equivalent in computer science, artificial intelligence, software engineering or a related discipline.
• Equivalent professional experience demonstrating comparable expertise is accepted. Non-traditional paths are welcome when they demonstrate clear impact.

Working context

• Multidisciplinary setup combining internal and external colleagues.
• Controlled development and validation precede potential operational deployment.
• Technical leadership relies on guidance and architecture decisions, without direct line management.