AWS GenAI Lead Engineer — Enterprise AI & Agents (Onsite)

Themesoft Inc; Charlotte (NC); On-site; USD 140,000 - 180,000; Full time

Job summary

The Themesoft Inc Charlotte, NC team is seeking an AWS GenAI Lead Engineer to analyze business requirements and design intelligent agent workflows. The role combines hands-on engineering with technical leadership across the AWS AI ecosystem in an onsite contract setting.

You will work with Python, FastAPI, and LangChain/LangGraph to build secure, scalable agentic applications, with emphasis on retrieval-augmented generation, tooling, and production deployment.

Qualifications

• 8+ years software engineering experience with Python and AWS cloud-native patterns.
• 2+ years AI/ML or Generative AI engineering with production LLM apps.
• Hands-on with AWS Bedrock and foundation-model integration.
• Experience with Strands Framework and LangChain or LangGraph.
• Strong FastAPI, REST API, asynchronous programming and microservices development.
• Experience with RAG, prompts, vector databases, embeddings, semantic search.
• Knowledge of Docker, CI/CD, IaC, logging and secure production deployment.
• Excellent stakeholder communication and technical leadership.
• AWS certifications preferred.

Responsibilities

• Analyze business requirements and design intelligent agent workflows.
• Deliver secure, scalable, enterprise-grade agentic applications.
• Provide technical leadership across the AWS AI ecosystem.
• Mentor team members and coordinate with stakeholders.
• Implement production-ready AI solutions with monitoring and testing.

Skills

Python

AWS Bedrock

Strands Framework

LangChain

LangGraph

FastAPI

REST API

Docker

CI/CD

Tools

Docker

CI/CD

Job description

The Themesoft Inc Charlotte, NC team is seeking an AWS GenAI Lead Engineer to analyze business requirements and design intelligent agent workflows. The role combines hands-on engineering with technical leadership across the AWS AI ecosystem in an onsite contract setting.

You will work with Python, FastAPI, and LangChain/LangGraph to build secure, scalable agentic applications, with emphasis on retrieval-augmented generation, tooling, and production deployment.