Gen AI - Data Engineer with AWS Experience

Capgemini is seeking a Gen AI Data Engineer with hands-on AWS experience to architect, build, and scale AI-powered “Store AI Agents” that support store operations. In this onsite contract role in Dallas, you will take solutions from architecture through production, combining agentic AI and GenAI engineering with data and platform design.

Key Responsibilities

• Own end-to-end architecture and implementation of Store AI Agents.
• Design agentic workflows that connect LLMs with APIs, databases, backend services, enterprise applications, and MCP servers.
• Build and tune RAG capabilities, including embeddings, retrieval, vector search, grounding, and context management.
• Define onboarding and integration processes for new AI agents, covering testing, deployment, monitoring, and production readiness.
• Establish system boundaries between LLM reasoning/generation and deterministic backend services.
• Apply Lakehouse / Medallion architecture (Bronze, Silver, Gold) to enable AI and data use cases.
• Set scalable strategies for AI and RAG testing, validation, observability, and performance optimization.
• Contribute to production readiness by addressing latency, context limits, retrieval quality, scalability, and reliability.
• Provide technical leadership across AI/ML, data engineering, cloud, application, and business teams.

Requirements

• Proven delivery of at least one end-to-end LLM, RAG, or Agentic AI project.
• Strong architectural and practical experience with Generative AI on AWS.
• Hands-on knowledge of LLMs, RAG, embeddings, vector search, and agentic workflows.
• Experience integrating AI agents with APIs, databases, backend services, and enterprise systems.
• Understanding of MCP (Model Context Protocol) and agent-to-tool or service integration.
• Experience using Lakehouse and Medallion Architecture, including data pipeline optimization.
• Solid understanding of AI testing, observability, security, scalability, latency, and production performance.
• Ability to clearly explain end-to-end architecture, technology selections, integration patterns, and design trade-offs.

Technologies

• AWS
• LLMs
• RAG
• Embeddings
• Vector search
• MCP (Model Context Protocol)
• Lakehouse
• Medallion Architecture

Location and Contract Details

• Location: Dallas, TX, United States (onsite)
• Compensation: USD 37 - 59 per hour
• Job type: Contract

Benefits

• Medical
• Dental
• Vision
• Retirement benefits

Preferred

• Experience with AWS-based GenAI and data platforms.
• Experience building enterprise-scale AI agents or multi-agent solutions.
• Exposure to modern vector databases, Lakehouse technologies, and AI orchestration frameworks.
• Strong technical leadership and stakeholder communication skills.