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# Generative AI Engineer - Agentic Systems

- **Company:** ConglomerateIT LLC
- **Location:** Dallas, TX, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Business Software, Databases, DevOps, Graph Database, Software Engineering, Chatbots, LangChain, ReactJS, Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, Prompt Engineering, AgentCore, Generative AI, Indexer, Agentic-AI, Gitlab, Infrastructure Automation Frameworks, Information Technology, Restful APIs, Model Context Protocol, Terraform, Human in the Loop, AI Co-pilot, Microservices
- **Published:** October 22, 2026
- **Apply:** https://www.careerjet.com/jobad/us7c28069689e610be953eeaddb813472c

## About the Role

* 7+ years in software engineering, with a strong track record in AI/ML.
 * 4+ years hands-on with Generative AI, LLMs, and RAG.
 * 2+ years building agentic or multi-agent systems.
 * Proven experience shipping production AI apps in the cloud.
 * Bachelor's or Master's in Computer Science, Engineering, AI, Data Science, or a related field.

Nice to Have

 * Built enterprise AI copilots or conversational assistants.
 * Advanced orchestration experience with LangGraph.
 * Used frameworks to evaluate, test, and benchmark AI agents.
 * Worked with knowledge graphs and graph-based reasoning.
 * Set up Human-in-the-Loop (HITL) workflows.

## Description

We're looking for a seasoned engineer to build and launch enterprise-level AI solutions powered by Generative AI and autonomous agents. You'll work hands-on with AWS Bedrock, AgentCore, LangGraph, LangChain, MCP, and RAG to bring smart, production-ready applications to life.
What You'll Do
Agent Development

 * Architect and build single-agent and multi-agent systems on AWS AgentCore.
 * Create and fine-tune agent workflows with LangGraph and LangChain.
 * Give agents the ability to plan, reason, use tools, and retain memory.
 * Define how agents talk to each other and to outside systems.
 * Work with Model Context Protocol (MCP) and tool-calling designs.

RAG & GenAI Solutions

 * Build large-scale RAG pipelines using AWS Bedrock foundation and embedding models.
 * Shape the approach for vectorization, indexing, retrieval, re-ranking, and grounding.
 * Set up prompt engineering frameworks and methods to evaluate GenAI output.
 * Deliver chatbots, knowledge assistants, copilots, and AI-driven automation.
 * Apply Bedrock Guardrails to keep solutions safe, compliant, and responsible.

Apps, APIs & Integration

 * Expose AI features to enterprise apps through RESTful APIs.
 * Connect agents to business apps, workflows, databases, and third-party systems.
 * Build clean, easy-to-use front ends with React and modern UI tools.
 * Create reusable, scalable AI services and microservices.

Cloud & DevOps

 * Deploy and run AI solutions on AWS using Infrastructure as Code practices.
 * Build and maintain infrastructure with Terraform.
 * Set up and manage CI/CD pipelines in GitLab.

Standards & Collaboration

 * Set best practices, standards, and reference designs for GenAI and agentic work.
 * Partner with product owners, architects, data engineers, and business teams.
 * Make sure every solution meets security, governance, compliance, and responsible AI needs.