Gen AI - Data Engineer with AWS Experience
Backend Developer
Agentic Ai
Ai Agent
Ai Agent Platform
Ai Platform
Ai Security
Artificial Intelligence
Artificial Intelligence Engineer
Cloud Operations
Data Analysis
Data Analytics
Data Architecture
Data Engineer
Data Integration
Data Integration Tools
Data Lakehouse
Data Pipeline
Data Platform
Data Processing
Databases
Databricks Lakehouse
Engineer
ETL
Generative AI
Informatica
Programming
Rag Architectures
Software Development
Vector Databases
Job Description
Capgemini is seeking a contract Gen AI - Data Engineer with AWS experience to architect, build, and scale AI-powered “Store AI Agents” that support store operations. The role blends hands-on development with technical leadership across agentic AI, RAG, and production-grade AWS delivery.
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 onboarding and integration processes for new AI agents, covering testing, deployment, monitoring, and production readiness.
- Establish a clear system architecture that separates LLM reasoning and generation from deterministic backend services.
- Leverage Lakehouse and Medallion architecture (Bronze, Silver, Gold) to enable AI and data use cases.
- Define scalable approaches for AI and RAG testing, validation, observability, and performance optimization.
- Handle production challenges such as latency, context limitations, retrieval quality, scalability, and reliability.
- Provide technical leadership across AI and ML, data engineering, cloud, application, and business teams.
Requirements
- Proven 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 agent-to-tool or service integration.
- Experience with Lakehouse and Medallion Architecture, including data pipeline optimization.
- Strong understanding of AI testing, observability, security, scalability, latency, and production performance.
- Ability to articulate end-to-end architecture, including 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 hourly
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.