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Job Description

Capgemini is seeking a contract Data Engineer with AWS experience to architect, build, and scale AI-powered “Store AI Agents” that support store operations. This role blends hands-on engineering with technical leadership, taking GenAI solutions from architecture through production readiness using agentic workflows and RAG capabilities.

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 optimize RAG solutions, including embeddings, retrieval, vector search, grounding, and context management.
  • Define how new AI agents are onboarded and integrated, including testing, deployment, monitoring, and production readiness.
  • Set the system architecture that separates LLM reasoning and generation from deterministic backend services.
  • Apply Lakehouse/Medallion architecture (Bronze, Silver, Gold) to enable AI and data use cases.
  • Create scalable approaches for AI/RAG testing, validation, observability, and performance optimization.
  • Handle production engineering concerns such as latency, context limitations, retrieval quality, scalability, and reliability.
  • Provide technical leadership across AI/ML, data engineering, cloud, application, and business teams.

Required Qualifications

  • Demonstrated experience delivering at least one end-to-end LLM, RAG, or agentic AI project.
  • Strong architectural and hands-on 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 how agent-to-tool or service integration is implemented.
  • Experience with Lakehouse and Medallion Architecture, plus data pipeline optimization.
  • Strong grasp of AI testing, observability, security, scalability, latency, and overall production performance.
  • Ability to clearly explain end-to-end architecture, technology choices, integration patterns, and design trade-offs.

Technologies

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

Location and Employment Details

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

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.

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