Agentic AI Engineer

JOB DESCRIPTION:
Title: Agentic AI Engineer – Generative AI & Agentic Systems
Location: Dallas, TX
Duration: Long term
Rate: $60 on corp to corp
2 rounds of face to face
4-5 days work from office in a week

Summary
We are seeking an experienced Agentic AI Engineer to design, develop, and deploy
enterprise-grade Generative AI and Agentic AI solutions. The ideal candidate will have deep
expertise in building AI-powered applications using AWS Bedrock, AgentCore,
LangGraph, LangChain, MCP and Retrieval-Augmented Generation
(RAG) architectures.
Key Responsibilities
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.
Required Qualifications
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.
Preferred Qualifications
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.