Join Capgemini Engineering, a global leader in engineering services, and be at the forefront of innovation. We are seeking an experienced GenAI & Agentic AI Lead/Architect to drive the development and implementation of cutting-edge AI solutions for enterprise clients. This is an opportunity to make a significant impact within a dynamic and collaborative environment, working on projects that shape the future of technology.

At Capgemini, you'll have the chance to shape your career path with diverse opportunities and personalized guidance from leaders. We offer comprehensive wellness benefits and the chance to work on transformative projects that address both business and societal challenges.

Architect and lead the design of GenAI and Agentic AI solutions for large-scale enterprise environments, spanning technologies like J2EE, .NET, and ERP.

Develop comprehensive end-to-end AI architectures, critically evaluate design alternatives, and conduct cost-benefit analyses for technology decisions.

Champion GenAI innovation through proof-of-concepts, pilot projects, and the creation of reusable assets, while actively adopting emerging AI technologies and platforms.

Provide strategic technology roadmaps, architectural recommendations, and hands-on implementation guidance to delivery teams.

Engage effectively with stakeholders through clear communication, impactful presentations, and robust cross-functional collaboration.

We are looking for a seasoned professional with 9 to 12 years of IT experience, demonstrating deep expertise in GenAI architecture, cloud AI platforms, Python-based AI/ML development, and designing enterprise-scale solutions.

Key technical proficiencies include Prompt Engineering, RAG, LangChain, Vector Databases, Text/Image Generation, and AI Agent frameworks. Strong programming skills in Python, with libraries such as Pandas, NumPy, Matplotlib, and Scikit-learn, are essential, alongside experience in data preprocessing and feature engineering.

Familiarity with cloud AI platforms like Azure OpenAI, AWS Bedrock, and GCP AI Services, along with the deployment of GenAI applications on cloud infrastructure, is crucial. Experience with application development frameworks like FastAPI, Flask, Streamlit, API integration, and production deployment of AI solutions is also required. Proficiency in data and platform skills, including PostgreSQL, SQL/PL-SQL, Cloud Storage, data ingestion, access control, key vaults, and security best practices, will be highly valued.