Industrial AI & Data Technical Lead

Overview

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.

We are seeking a visionary and hands-on AI & Data Science Lead to shape, drive, and deliver cutting-edge AI initiatives within a major digital transformation program. In this role, you will partner directly with client leadership to define their strategic AI vision, translate it into a tangible roadmap and scalable use-case pipeline, and ensure the successful delivery of high-impact AI solutions.

You will combine deep technical mastery
, strong industry insight (Oil & Gas and adjacent sectors), and leadership excellence to guide teams across the full hybrid-intelligence spectrum – spanning Generative AI, Machine Learning, physics-based simulation, IoT, and cloud platforms. You will play a central role in shaping our growing AI capability and driving a culture of innovation, collaboration, and engineering excellence.

• Shape and articulate the client’s long-term AI vision and translate it into an actionable roadmap and prioritized use-case portfolio.
• Engage with senior stakeholders to identify business opportunities where AI delivers measurable operational, financial, or safety impact.
• Serve as a trusted advisor, guiding clients through AI adoption, scaling challenges, and governance considerations.

• Define technical architectures for scalable, production-ready AI systems across Generative AI, ML, physics-based models, and IoT-enabled intelligence.
• Ensure engineering excellence in solution design, integration, and deployment across hybrid cloud and edge environments.
• Act as the technical authority overseeing key decisions, ensuring use cases are implemented using state-of-the-art approaches.
• Deep familiarity with IT/OT integration, including SCADA, DCS, historians, and real-time operational data management in industrial environments.
• Hands-on experience designing or deploying AI/ML solutions across cloud, on-premise, and edge compute environments, ensuring performance, reliability, and cybersecurity for industrial use cases.
• Understanding of industrial connectivity, sensor networks, and asset-level telemetry to support physics-based and ML-driven intelligence.

• Lead end-to-end delivery of AI use cases from ideation and prototyping to MLOps-enabled industrialization.
• Champion agile engineering practices, quality standards, and continuous improvement.
• Ensure successful deployment, adoption, and measurable value realization.

• Build, mentor, and scale a high-performing AI team with a culture of innovation, ownership, and collaboration.
• Foster cross-functional teaming across data scientists, AI engineers, software engineers, and domain SMEs.
• Contribute to the development of Capgemini’s global AI practice via accelerators, frameworks, and reusable assets.

• Bachelor’s or Master’s degree in Computer Science, AI, Data Science, Engineering, or a related field.
• 8+ years of experience in AI/ML leadership roles, including client-facing delivery.
• Proven experience shaping AI strategies, roadmaps, and complex multi-year transformation programs.
• Strong industry background in Oil & Gas; adjacent experience in Energy, Utilities, or Industrial Manufacturing is a plus.
• Demonstrated track record building and leading multidisciplinary AI/ML teams.
• Deep understanding of cloud ecosystems (GCP preferred; AWS acceptable) and enterprise data platforms.
• Hands-on experience across Generative AI, Machine Learning, and physics-based or simulation-driven analytics.
• Solid understanding of agile delivery, product mindset, and engineering best practices.
• Experience collaborating with executive stakeholders in business and IT.