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Skills
AWS Lambdaunmatched
Amazon Simple Storage Service (S3)unmatched
Amazon Web Services (AWS)unmatched
Application Programming Interface (API)unmatched
Artificial Intelligence (AI)unmatched
Automationunmatched
Cloud Computingunmatched
Continuous Deployment/Deliveryunmatched
Continuous Integrationunmatched
DevOpsunmatched
Dockerunmatched
Error Handlingunmatched
Gitunmatched
Health Planunmatched
IDE (Integrated Development Environment)unmatched
Information Technology Consultingunmatched
JSONunmatched
JavaScriptunmatched
Microsoft Windows Azureunmatched
Node.jsunmatched
Python Programming/Scripting Languageunmatched
REST (Representational State Transfer)unmatched
React.jsunmatched
Semantic Reasonerunmatched
Standards Developmentunmatched
Web Programmingunmatched
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.