What are the responsibilities and job description for the Google Cloud Platform AI Engineer position at Compugra Systems?
Google Cloud Platform AI Engineer
Location : Irving, TX, or Charlotte (100% Onsite)
1 Year
Have a strong foundation in Java and Python, coupled with hands-on experience using Google's AI tools
AI Agent Development: Design, build, and deploy autonomous AI agents capable of reasoning, planning, and executing complex workflows.
LLM Integration: Integrate cutting-edge Large Language Models (LLMs) into our core products and services to enhance functionality and user experience.
Model Context Protocol (MCP) Implementation: Utilize the Model Context Protocol (MCP) to securely connect our AI models to various data sources, tools, and development environments.
Automated Code Generation: Leverage AI and LLMs to build systems that assist in, or fully automate, code generation, testing, and optimization processes.
System Engineering: Write clean, scalable, and maintainable code in both Java and Python to support AI backend infrastructure.
Google Ecosystem Integration: Utilize Google ADK (AI Developer Kits) and related Google Cloud AI services (e.g., Vertex AI, Gemini APIs) to deploy robust AI solutions.
Cross-Functional Collaboration: Work closely with product managers, data scientists, and frontend engineers to translate business requirements into technical AI solutions.
Must-Have Qualifications:
Programming Languages: Strong proficiency in both Java and Python, with a proven track record of building production-grade software.