Enterprise AI Solutions Architect
Pubblicato il 17-10-2026 - Capgemini Engineering in Piemonte
- Experience designing enterprise AI, ML or GenAI solutions;
At Capgemini Engineering, the world leader in engineering services, we bring together a global team of engineers, scientists, and architects to help the world's most innovative companies unleash their potential. From autonomous cars to life-saving robots, our digital and software technology experts think outside the box as they provide unique R&D; and engineering services across all industries. Join us for a career full of opportunities. Where you can make a difference. Where no two days are the same.
YOUR ROLE
As an Enterprise AI Solutions Architect at Capgemini Engineering you will be responsible for design and govern secure, scalable and production-ready AI and GenAI solutions. The role combines architecture leadership with practical knowledge of AI technologies, supporting engineering teams and translating business needs into sustainable technical solutions.
- Define end-to-end architectures for AI and GenAI solutions;
- Design AI-enabled applications, agentic workflows and orchestration patterns;
- Select suitable models,
platforms, frameworks and integration approaches;
- Establish standards for AI governance, security, responsible AI and compliance;
- Guide engineering teams during implementation, integration and deployment;
- Ensure AI solutions are observable, scalable, reliable and cost-aware;
- Lead architecture reviews and communicate options and trade-offs to stakeholders.
YOUR PROFILE
- 5+ years in solution architecture, data architecture, AI architecture or related roles;
- Experience delivering production-grade AI, ML or GenAI solutions;
- Experience working across technical and business teams in complex environments.
- Experience designing enterprise AI, ML or GenAI solutions;
- Strong understanding of LLMs, RAG, AI agents and orchestration patterns;
- Knowledge of AI application architecture, APIs and cloud-native integration;
- Understanding of model evaluation, monitoring and lifecycle