Responsibilities: Design, develop, and support cloud-native automation and Al agent workflows using Python and LLM orchestration frameworks (LangChain / LangGraph), deployed on AWS using containerized architectures. Agentic RAG 2.0: Develop "iterative retrieval" systems where agents autonomously decide if they have enough information or if they need to perform additional searches/queries.
Numbers & Facts
Location
Detroit, MI
Description
Our client, a IT Services and Consulting company, is looking for a Agentic AI Engineer for their Detroit, MI/ Charlotte, NC/Hybrid location.
Responsibilities:
Design, develop, and support cloud-native automation and Al agent workflows using Python and LLM orchestration frameworks (LangChain / LangGraph), deployed on AWS using containerized architectures.
Develop automation solutions using Python.
Build Al agents using LangChain and LangGraph to orchestrate tools, APls, and workflows.
Integrate automations with enterprise systems via REST APIs and databases.
Containerize services using Docker and support CI/CD pipelines.
Deploy and operate solutions on AWS (IAM, S3, Lambda, ECS/Fargate, CloudWatch).
Reasoning Engines: Experience with frontier models like GPT-4o, Claude 3.5, and Llama 3.x/4 specifically for tool-calling and JSON-mode outputs
Azure OpenAI proficiency .
Agentic RAG 2.0: Develop "iterative retrieval" systems where agents autonomously decide if they have enough information or if they need to perform additional searches/queries.
Implement logging, error handling, and basic monitoring.
Collaborate with onshore architects and follow defined architecture standards
Requirements:
Python (automation, backend services).
JavaScript (React/Node JS)
LangChain and/or LangGraph hands-on experience.
Docker and container-based deployments.
AWS Cloud Practitioner-level knowledge with hands-on exposure.