AI Architect
Employment Information
Job Description
AI Architect responsible for designing and integrating innovative AI solutions at Inetum. Leading complex international projects in AI across various sectors.
Responsibilities:
- Design and document technical architectures for AI solutions (Machine Learning, Deep Learning, NLP, Computer Vision, LLM, AI Agents, etc.) considering security, scalability, costs and performance constraints.
- Define and drive the AI technology roadmap in collaboration with business, IT, and innovation teams.
- Select appropriate technologies, frameworks, and tools (TensorFlow, PyTorch, Azure ML, AWS SageMaker, Hugging Face, LangChain/Graph, N8n, …).
- Ensure the coherence, robustness, and maintainability of deployed solutions.
- Participate in solutions development.
- Mentor and support teams of Data Scientists, Data Engineers, and AI developers.
- Conduct technology watch and evaluate new AI market trends.
- Lead the integration of AI solutions in cloud, hybrid, or on-premise environments.
- Implement best practices for data governance, MLOps, and model management.
- Ensure compliance with security standards, regulations (GDPR, NIS2), and AI ethics.
- Collaborate with technology partners and clients to maximize the value of AI solutions.
- Participate in drafting technical proposals and responding to RFPs.
Requirements:
- Master’s degree or engineering diploma in Computer Science, Applied Mathematics, Artificial Intelligence, or related field.
- Minimum 7 years of experience in designing and deploying AI solutions in enterprise environments.
- Mastery of AI architectures (supervised, unsupervised models, neural networks, NLP, Computer Vision, etc.).
- Expertise in leading AI tools and frameworks: TensorFlow, PyTorch, Scikit-learn, Keras, MLflow, etc.
- Expertise in major LLM vendors: OpenAI, Google Gemini, Anthropic, Meta, Mistral AI, AWS Bedrock, DeepSeek, Cohere, ...
- Expertise in developing Collaborative/Swarm of AI Agents/Agentic AI system.
- Experience with cloud AI platforms: Azure ML, AWS SageMaker, Google AI Platform.
- Strong knowledge of MLOps practices, CI/CD, and model lifecycle management.
- Proficiency in Python, R, SQL, and collaborative development environments (Git, Docker, Kubernetes).
- Deep understanding of security, compliance (NIS2, GDPR), and AI ethics.
- Ability to design hybrid architectures and integrate AI into existing systems.
- Knowledge in deploying on prem/sovereign AI solution set.
- Leadership and ability to unite and guide multidisciplinary teams.
- Innovative mindset and technological curiosity.
- Excellent communication, presentation, and simplification skills.
- Rigor, organizational skills, and results-oriented approach.
- Fluent in English (French is a plus).
Benefits:
- Full access to foreign language learning platform
- Personalized access to tech learning platforms
- Tailored workshops and trainings to sustain your growth
- Medical subscription
- Meal tickets
- Monthly budget to allocate on flexible benefit platform
- Access to 7 Card services
- Wellbeing activities and gatherings
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