AI Agent Engineer (LLMs | RAG | Autonomous Agents | Azure AI)

Hybrid in Austin, TX, US • Posted 17 hours ago • Updated 17 hours ago
Contract Independent
Contract W2
No Travel Required
Hybrid
Depends on Experience
Fitment

Dice Job Match Score™

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Job Details

Skills

  • AI/ML Engineering
  • Data Science
  • Autonomous Agents
  • AI Agent Development
  • Retrieval Augmented Generation
  • RAG Architecture
  • Vector Databases
  • Pinecone
  • FAISS
  • Weaviate
  • ChromaDB
  • LangChain
  • LangGraph
  • CrewAI
  • AutoGPT
  • Context Engineering
  • Prompt Engineering
  • Large Language Models
  • LLM Integration
  • OpenAI API
  • Hugging Face
  • Azure AI
  • Python
  • Machine Learning Libraries
  • Natural Language Processing
  • NLP
  • API Integration
  • Multi-Agent Systems
  • Agentic Workflows
  • Model Context Protocol
  • MCP
  • AI Governance
  • AI Guardrails
  • Content Filtering
  • Responsible AI
  • Data Privacy
  • PII
  • PHI
  • Secure Data Handling
  • Model Lifecycle Management
  • MLOps
  • AI Deployment
  • Scalable AI Systems
  • Cloud AI
  • Performance Optimization
  • Token Optimization
  • Cost Optimization
  • Enterprise AI Architecture

Summary

Highly skilled AI Agent Engineer to design, build, and deploy enterprise-grade AI solutions leveraging autonomous agents and Retrieval-Augmented Generation (RAG). This role focuses on developing scalable, secure, and cost-efficient AI systems that enhance business processes and decision-making.

You will collaborate closely with developers, UX designers, and business stakeholders to deliver production-ready AI applications with strong governance, security, and performance standards.

Key Responsibilities:

  • Design and develop AI-powered autonomous agent systems
  • Build and optimize RAG architectures using vector databases
  • Implement context engineering strategies for LLM performance
  • Integrate LLMs via APIs and AI platforms (Azure AI, OpenAI, etc.)
  • Develop and enforce AI governance, guardrails, and safety controls
  • Ensure secure handling of sensitive data (PII/PHI)
  • Optimize LLM cost, token usage, and system performance
  • Support scalable, enterprise-grade AI deployments

Required Experience:

  • 4+ years in AI/ML engineering or advanced data science
  • Hands-on experience building production-grade autonomous agents
  • Strong expertise in LangChain, LangGraph, CrewAI, or AutoGPT
  • Deep experience with RAG and vector database architectures
  • Proficiency in Python and AI/ML frameworks
  • Experience with MCP, AI governance, and model lifecycle management

Preferred:

  • Multi-agent workflow design
  • LLM optimization (cost, latency, efficiency)
  • Enterprise AI scalability and deployment patterns
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: 10530359
  • Position Id: 8930461
  • Posted 17 hours ago
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