Join Capgemini, a global leader in business and technology transformation, to drive Industry 4.0 and AI advancements for leading manufacturing and industrial organizations. This role is for a visionary technology leader who bridges the factory floor and AI frontiers, capable of implementing scalable, responsible, and outcome-driven AI solutions.

Capgemini Engineering offers a collaborative environment where innovation and cutting-edge technologies converge to create significant impact. We empower organizations to harness innovation and achieve sustainable business outcomes through expertise in Digital Manufacturing, AI, Data, Cloud, and Industry 4.0.

Lead the design and delivery of AI-driven solutions for manufacturing and industrial clients, combining industry expertise, AI innovation, solution architecture, consulting, and business transformation.

Key responsibilities include: - Leading AI solution architecture, client engagements, and AI transformation initiatives. - Driving measurable operational outcomes such as productivity improvement, cost reduction, quality enhancement, and operational efficiency gains. - Growing the AI-driven business pipeline and revenue. - Developing reusable assets and industrial AI accelerators to increase AI adoption across operations.

A minimum of 10–18 years of experience is required, with at least 7 years in Manufacturing, Industrial Operations, Digital Manufacturing, Industry 4.0, or Industrial Digital Transformation.

Demonstrated expertise in designing and deploying AI, Machine Learning, Advanced Analytics, or Generative AI solutions for over 3 years is essential. Proven success in deploying AI solutions into production and achieving measurable client outcomes is critical.

Qualifications include a Bachelor's or Master's degree in Engineering, Computer Science, Industrial Engineering, Data Science, or a related field. Strong technical skills encompass Generative AI, LLMs (GPT, Claude, Gemini, Llama), Prompt Engineering, Agentic AI, Multi-Agent Systems, Python, FastAPI, REST APIs, Microservices, RAG, Vector Databases, Embeddings, and cloud AI platforms (Azure, AWS). Familiarity with AI governance, observability, security, and responsible AI practices is also expected.