About the Role
As an AI Field Data Engineer at Capgemini Engineering, you will sit at the intersection of cutting-edge AI innovation and real-world business impact. Embedded directly with our most strategic customers, you will translate complex, ambiguous challenges into production-grade AI systems that deliver measurable outcomes. This is a role for someone who thrives at the frontier — building first-of-their-kind AI applications.
Responsibilities
•Designing end-to-end AI solutions by transforming ambiguous business problems into scalable, production-ready technical architectures — bridging the gap between customer needs and technical feasibility
•Building production GenAI applications, including multi-agentic solutions leveraging technologies such as Agent Bricks, Genie, LangChain, DSPy and HuggingFace, with a strong focus on evaluation and optimisation
•Delivering and managing ML models in production using MLflow and MLOps best practices across cloud platforms including AWS, Azure or GCP, ensuring robust, reliable and performant deployments
•Shaping customer AI product vision by working consultatively with strategic clients to define AI roadmaps grounded in technical feasibility and aligned to measurable business outcomes
•Establishing best practices for AI engineering, contributing to the development of reusable frameworks
Requirements
•4+ years of hands-on experience in Machine Learning, Generative AI, MLOps and Software Engineering, with a proven track record of delivering productionised models and AI systems
•Proficiency in GenAI tooling and frameworks, including LangChain, DSPy and HuggingFace, with practical experience building and deploying multi-agentic solutions in real-world environments
•3+ years of customer-facing consulting experience, with the ability to communicate complex technical concepts clearly and build trusted relationships with strategic stakeholders
•Solid cloud and MLOps experience across one or more of AWS, Azure or GCP, with demonstrated use of MLflow for model tracking, versioning and deployment
•A graduate degree in a quantitative field such as Computer Science, Mathematics, Statistics, Engineering or a related discipline
Conditions & Benefits
•Yearly financial bonus
•Private medical care with Medicover, with additional packages (e.g., dental, senior care, oncology) available on preferential terms
•Life insurance and access to the NAIS benefit platform
•Access to over 70 training tracks with certification opportunities (e.g., GenAI, Excel, Business Analysis, Project Management) on the NEXT platform
•Free access to Education First languages platform, TED Talks and Udemy Business materials and trainings
•Work with cutting-edge technology at the forefront of IT innovation, with Capgemini partnering with top global enterprises, including 145 Fortune 500 companies
•Hybrid working model: after onboarding, work from a modern office combined with ergonomic home office (home office package including laptop, monitor, and chair) — ask your recruiter for details
