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# Agentic AI Engineer - Generative AI & Agentic Systems

- **Company:** Robotics Technologies LLC
- **Location:** Chicago, IL, United States
- **Experience:** Experienced
- **Salary:** $156,000
- **Contract:** Temporary contract
- **Skills:** LangGraph Framework, Artificial Intelligence, Amazon Web Services, Architectural Patterns, Business Software, Databases, Memory Management, Graph Database, Machine Learning, Software Engineering, Enterprise Software Applications, Cloud Platform System, ReactJS, Large Language Models, Multi-Agent Systems, Prompt Engineering, AgentCore, Generative AI, Indexer, Infrastructure as Code (IaC), Agentic-AI, Gitlab, AI Platforms, Information Technology, Front End Software Development, Virtual Agents, Restful APIs, Model Context Protocol, Terraform, Human in the Loop, AI Co-pilot, Microservices
- **Published:** November 8, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=a02446ab65b2f394

## About the Role

Bachelor's or Master's degree in Computer Science, Engineering, Artificial Intelligence, Data Science, or a related field.
7+ years of software engineering experience, including significant experience building AI/ML solutions.
4+ years of hands-on experience with Generative AI, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG) architectures.
2+ years of experience designing and implementing Agentic AI or multi-agent systems.
Experience deploying production-scale AI applications in cloud environments., Experience building enterprise AI copilots and conversational assistants.
Experience with advanced orchestration workflows using LangGraph.
Experience with AI agent evaluation, testing, and benchmarking frameworks.
Experience with knowledge graph integrations and graph-based reasoning.
Experience implementing Human-in-the-Loop (HITL) workflows.

## Description

Design and develop autonomous and multi-agent AI systems using AWS AgentCore capabilities
Build and optimize agent workflows using LangGraph and LangChain.
Implement planning, reasoning, tool usage, and memory management capabilities within AI agents.
Design agent-to-agent and agent-to-system interaction patterns.
Experience of MCP (Model Context Protocol) and tool-calling architectures.
Build enterprise-scale Retrieval-Augmented Generation (RAG) solutions using AWS Bedrock foundation models and embedding models.
Design vectorization, indexing, retrieval, re-ranking, and grounding strategies.
Develop prompt engineering frameworks and evaluation methodologies for GenAI applications.
Implement conversational AI, knowledge assistants, copilots, and AI-powered automation solutions.
Integrate Bedrock Guardrails to ensure safety, compliance, and responsible AI practices.
Design and develop RESTful APIs to expose AI capabilities to enterprise applications.
Integrate AI agents with business applications, enterprise workflows, databases, and external systems.
Develop intuitive front-end experiences using React and modern UI frameworks.
Build scalable and reusable AI services and microservices.
Deploy and manage AI solutions on AWS using Infrastructure as Code (IaC) principles.
Develop and maintain infrastructure using Terraform.
Implement CI/CD pipelines using GitLab.
Define best practices, standards, and architectural patterns for GenAI and Agentic AI implementations.
Collaborate with product owners, architects, data engineers, and business stakeholders.
Ensure AI solutions adhere to security, governance, compliance, and responsible AI requirements.