AI Engineer

Quick Facts

• Role: AI Engineer

• Location: Irving, TX or Charlotte, NC (100% onsite)

Description

You will design, build, and deploy autonomous AI agents and integrate Large Language Models (LLMs) into products and services. The role focuses on implementing Model Context Protocol (MCP) for secure connectivity to data sources and tools, and on enabling automated code generation and software automation. You’ll write maintainable AI backend code in Java and Python and use Google AI tools and services to deploy solutions.

Responsibilities

• Design, build, and deploy autonomous AI agents that can reason, plan, and execute complex workflows

• Integrate LLMs into core products and services to improve functionality and user experience

• Implement MCP to securely connect AI models to data sources, tools, and development environments

• Leverage AI/LLMs to assist with or fully automate code generation, testing, and optimization processes

• Write clean, scalable, and maintainable Java and Python code for AI backend infrastructure

• Use Google ADK and related Google Cloud AI services (Vertex AI, Gemini APIs) to deploy AI solutions

• Collaborate with product managers, data scientists, and frontend engineers to translate business requirements into technical AI solutions

Requirements

• Strong proficiency in both Java and Python with a proven track record building production-grade software

• Hands-on experience with Google ADK (or equivalent Google Cloud AI / Vertex AI tools)

• Practical LLM expertise, including prompt engineering, fine-tuning, and RAG architectures

• Demonstrable experience building and orchestrating AI agents (LangChain, LangGraph, or custom implementations)

• Familiarity and practical experience with Model Context Protocol (MCP) for standardizing AI interactions with external tools

• Experience leveraging AI tools or building pipelines for code generation and software automation

Benefits

Not specified in the provided posting.