AI Engineer -Data Scientist

Capgemini • Chicago, ND

1d • $76,730 - $150,800 • Hybrid

About The Position

Capgemini is seeking a GenAI Engineer / Data Scientist to design, build, and deploy Generative AI and Predictive AI solutions that drive business value across enterprise environments. The role partners with business stakeholders, data engineers, architects, and application teams to develop AI-powered applications, agentic workflows, and intelligent automation solutions using modern cloud, MLOps, and data engineering practices. It is a hybrid role based in Houston, Texas; Dallas, Texas; Atlanta, Georgia; or Nashville, Tennessee.

Requirements

• At least 5 years of experience in Data Science, Machine Learning, Artificial Intelligence, or Advanced Analytics.
• Strong programming experience with Python and SQL.
• Experience developing and integrating REST APIs, JSON, HTTP protocols, and authentication/token-based security.
• Strong understanding of API integration, documentation, and enterprise application connectivity.
• Hands-on experience with Generative AI, Large Language Models (LLMs), and modern AI frameworks.
• Experience working with GPT, Claude, Stable Diffusion, and similar foundation models.
• Strong experience with LangChain and LLM orchestration frameworks.
• Experience developing machine learning solutions using TensorFlow and related AI/ML technologies.
• Knowledge of NLP, prompt engineering, embeddings, vector databases, and Retrieval-Augmented Generation (RAG).
• Experience designing and deploying AI agents and agentic workflows.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform (GCP).

Responsibilities

• Develop and implement Generative AI and Predictive AI models for enterprise use cases.
• Build AI solutions involving NLP, computer vision, classification, regression, and clustering techniques.
• Design and integrate AI applications using APIs, REST services, authentication frameworks, and cloud-native platforms.
• Develop AI agents, agentic workflows, and autonomous systems for process automation and decision-making.
• Implement Retrieval-Augmented Generation (RAG) and LLM-powered applications.
• Deploy, monitor, and optimize AI models in production environments using MLOps best practices.
• Design and maintain scalable data pipelines, data lakes, and data warehouse solutions.

Benefits

• Paid time off, including vacation (12–25 days depending on employee grade), company-paid holidays, personal days, and sick leave.
• Medical, dental, and vision coverage (or provincial healthcare coordination in Canada).
• Retirement savings plans, including 401(k) in the U.S. and RRSP in Canada.
• Life and disability insurance.
• Employee assistance programs.
• Other benefits as provided by local policy and eligibility.
• The role may be eligible for variable incentives, bonuses, or commissions, depending on position and applicable laws.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed