Gen AI Lead/Architect with AWS Experience

Dallas, TX, United States (On-site)

Contract (9 months 5 days)

Published 5 days ago

Lakehouse Architecture

LLMs

api integration

performance optimization

data engineering

RAG Optimization

Database Integration

Seeking a Store AI Agent Lead to architect, build, and scale AI-powered agents supporting store operations. The role requires strong hands-on experience with Agentic AI, LLMs, RAG, vector search, AWS, and enterprise system integration, along with the ability to take solutions from architecture through production.

Key Responsibilities:

-

Lead the end-to-end architecture and implementation of Store AI Agents.

-

Design agentic workflows integrating 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 the process for onboarding and integrating new AI agents, including testing, deployment, monitoring, and production readiness.

-

Establish clear architecture between LLM reasoning/generation and deterministic backend services.

-

Leverage Lakehouse/Medallion architecture (Bronze, Silver, Gold) to support AI and data use cases.

-

Define scalable approaches for AI/RAG testing, validation, observability, and performance optimization.

-

Address production challenges including latency, context limitations, retrieval quality, scalability, and reliability.

-

Provide technical leadership across AI/ML, data engineering, cloud, application, and business teams.

Required Skills & Experience:

-

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/service integration.

-

Experience with Lakehouse and Medallion Architecture and data pipeline optimization.

-

Strong understanding of AI testing, observability, security, scalability, latency, and production performance.

-

Ability to articulate end-to-end architecture, technology choices, integration patterns, and design trade-offs.

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.

The pay range that the employer in good faith reasonably expects to pay for this position is $37.91/hour - $59.23/hour. Our benefits include medical, dental, vision and retirement benefits. Applications will be accepted on an ongoing basis.