AI Engineer

Robotics Technologies; Texas; On-site; USD 78,000 - 112,000; Full time

Job summary

Robotics Technologies is hiring an AI Engineer to design, build, and deploy autonomous AI agents powered by LLMs and Google AI tooling. The role emphasizes secure tool integration via MCP and production-ready implementation across Java and Python.

You will integrate LLMs into core products, orchestrate AI agents with LangChain/LangGraph, and leverage Google ADK, Vertex AI, Gemini APIs to deliver robust AI solutions.

Qualifications

• Hands-on experience with Google ADK or equivalent Google Cloud AI tools.
• Deep practical comfort working with Large Language Models, including prompt engineering and fine-tuning.
• Demonstrable experience building and orchestrating AI Agents using LangChain, LangGraph, or equivalents.
• Familiar 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.

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.
• Use MCP to securely connect AI models to data sources, tools, and development environments.
• Apply AI capabilities to assist in, or fully automate, code generation, testing, and optimization processes.
• Develop clean, scalable, and maintainable code in Java and Python to support AI backend infrastructure.
• Utilize Google ADK and related Google Cloud AI services, including Vertex AI and Gemini APIs, to deploy robust AI solutions.
• Collaborate with product managers, data scientists, and frontend engineers to translate business requirements into technical AI solutions.

Skills

LLMs experience

Prompt engineering

RAG architectures

Tools

Google ADK

Vertex AI

Gemini APIs

LangChain

LangGraph

MCP

Java

Python

Job description

The AI Engineer role at Robotics Technologies focuses on the design, build, and deployment of autonomous AI agents powered by LLMs and Google AI tooling. The position emphasizes practical agent engineering, secure tool integration via MCP, and production-ready implementation across Java and Python.

Key Responsibilities

• Design, build, and deploy autonomous AI agents that can reason, plan, and execute complex workflows.
• Integrate Large Language Models (LLMs) into core products and services to improve functionality and user experience.
• Use the Model Context Protocol (MCP) to securely connect AI models to data sources, tools, and development environments.
• Apply AI and LLM capabilities to assist in, or fully automate, code generation, testing, and optimization processes.
• Develop clean, scalable, and maintainable code in Java and Python to support AI backend infrastructure.
• Utilize Google ADK (AI Developer Kits) and related Google Cloud AI services, including Vertex AI and Gemini APIs, to deploy robust AI solutions.
• Collaborate with product managers, data scientists, and frontend engineers to translate business requirements into technical AI solutions.

Required Skills and Experience

• Hands-on experience with Google ADK (or equivalent Google Cloud AI / Vertex AI tools).
• Deep practical comfort working with Large Language Models, including prompt engineering, fine-tuning, and RAG architectures.
• Demonstrable experience building and orchestrating AI Agents, using frameworks such as LangChain, LangGraph, or equivalent custom implementations.
• Practical familiarity 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.

Technology Stack

• Java, Python
• Google ADK (AI Developer Kits)
• Vertex AI, Gemini APIs
• Large Language Models (LLMs)
• Model Context Protocol (MCP)
• LangChain, LangGraph
• Prompt engineering
• Fine-tuning
• RAG architectures

Location and Compensation

Location: Texas (onsite).
Pay: USD 69 per hour.