Lead AI Data Engineer (GenAI)

TL;DR

Lead AI Data Engineer (GenAI): Designing and developing enterprise-grade Agentic AI solutions to automate business processes with an accent on AI agent orchestration and scalable data pipelines. Focus on implementing RAG architectures, integrating LLMs using LangChain and LangGraph, and optimizing complex SQL data transformations.

Location: Hybrid in Charlotte, NC

Company

A strategic staffing and technical solutions provider focused on enhancing enterprise business processes.

What you will do

• Design and develop Agentic AI solutions using Google ADK, LangChain, and LangGraph.
• Build intelligent AI agents capable of observing and automating human workflows and business processes.
• Develop scalable Python-based backend services, AI pipelines, and orchestration workflows.
• Build and optimize ETL/ELT pipelines supporting structured and unstructured enterprise data.
• Implement Retrieval-Augmented Generation (RAG), tool integrations, and memory handling.
• Collaborate with Process Excellence, Operations, and Engineering teams to develop AI copilots.

Requirements

• 5–7 years of experience in AI Engineering, GenAI, Data Engineering, or Agentic AI development.
• Strong hands-on experience building AI agents and orchestration workflows.
• Advanced Python development skills and advanced SQL expertise (query optimization, window functions).
• Hands-on experience with Google ADK, LangChain, and/or LangGraph.
• Strong understanding of RAG architectures and enterprise LLM integrations.
• Must be able to work in a hybrid environment in Charlotte, NC.

Nice to have

• Experience with cloud platforms such as GCP, AWS, or Azure.
• Experience with Kafka, Pub/Sub, Airflow, dbt, BigQuery, or Snowflake.
• Familiarity with vector databases and hybrid retrieval architectures.
• Experience implementing LLMOps, AI observability, and prompt management.
• Knowledge of enterprise AI governance, security controls, and PII handling.