AI Architect

Inetum is a European leader in digital services. Inetum’s team of 28,000 consultants and specialists strive every day to make a digital impact for businesses, public sector entities and society. Inetum’s solutions aim at contributing to its clients’ performance and innovation as well as the common good. 

Present in 19 countries with a dense network of sites, Inetum partners with major software publishers to meet the challenges of digital transformation with proximity and flexibility.  

Driven by its ambition for growth and scale, Inetum generated sales of 2.5 billion euros in 2023.  

TheSenior AI Architect will be responsible for defining the technological vision and leading the implementation of next‑generation Artificial Intelligence architectures. This role combines deep technical expertise, strategic thinking, and strong business alignment, ensuring that AI/GenAI solutions are scalable, secure, and deliver real impact.

Key Responsibilities

Architecture & Strategy

• Design thetarget architecture for AI ecosystems, includingCopilots/Agents, Azure OpenAI, AI Search, data platforms, integrations, and pipelines, ensuring end‑to‑end alignment with customer objectives.
• Definetechnical standards, guardrails, security practices, domain blueprints, and architectural guidelines, ensuring cross‑organizational consistency.
• Translate business needs into structured technical solutions, leadingworkshops, discovery sessions, and technical assessments.
• Assess trade‑offs between performance, cost, risk, and complexity when defining AI/GenAI solutions.

Technical Design & Implementation

• Lead the design ofscalable, secure, high‑performance AI/GenAI architectures.
• Select the appropriate technologies, frameworks, and models (LLMs, RAG, vector DBs, multi‑agent systems, MLOps, automation tooling).
• Build and validatePoCs and reference architectures to accelerate AI adoption.
• Integrate models, agents, and data pipelines withAPIs, microservices, core business applications, and enterprise data sources.

Governance, Quality & Security

• Establish principles fortechnical security, data isolation, compliance, observability, and model governance.
• Ensure adherence to best practices inperformance, resilience, scalability, and privacy.
• Define mechanisms forcontrol, auditability, and continuous improvement of AI architectures in production.
• Work closely with IT and Security teams to ensure consistent integration with the customer’s enterprise architecture.
• Ensure architectural consistency across multiple AI use cases and domains, particularly in large‑scale AI programs.

Technical Leadership & Collaboration

• Act as atechnical authority for internal and external stakeholders, including Data, Engineering, Product teams, and C‑level leadership.
• Mentor Data Scientists, ML Engineers, and Software Engineers, promoting technical excellence and best practices.
• Supportpre‑sales, RFPs, solution proposals, and technology vision for strategic clients.

• 6–10 years of experience in software development, solution architecture, data engineering, or AI.
• Solid experience inAI/ML and GenAI, including LLMs, pipelines, RAG, and enterprise integration.
• Strong knowledge of ML frameworks such asTensorFlow, PyTorch, Scikit‑learn.
• Significant experience withAzure (preferred), AWS or GCP, CI/CD, Docker/Kubernetes, and microservices.
• Strong understanding ofAI‑related security, cloud architectures, and MLOps practices.
• Excellent communication skills, both technical and non‑technical.
• Proven experience intechnical leadership and architectural standards definition.

• Experience in technology consulting and client interaction.
• Certifications such asAzure AI Engineer / Solution Architect, AWS ML Specialist, Google Cloud ML.
• Knowledge of architecture frameworks:TOGAF, DDD, Clean Architecture, SAFe.
• Participation in conferences, talks, orthought leadership initiatives.