GCP AI Engineer

Arkhya Tech Inc.; Irving (TX); On-site; USD 100,000 - 145,000; Full time

Job summary

Arkhya Tech Inc. is seeking an innovative AI Engineer to bridge software engineering and cutting‑edge AI. You will design, build, and deploy autonomous AI agents, work with LLMs, and drive automated code generation initiatives using Java and Python.

You will integrate Google AI tools (Vertex AI, ADK) and implement the MCP to securely connect AI models with data sources and tools. Collaboration with product managers, data scientists, and frontend engineers is essential to translate business needs

Qualifications

• Proficient in Java and Python with production-grade software experience.
• Hands-on with Google AI tools and Vertex AI or similar.
• Deep experience with LLMs, prompt engineering and RAG.
• Experience building AI agents and orchestration workflows.
• Knowledge of MCP for standardized AI interactions.
• Experience leveraging AI for code generation and automation.

Responsibilities

• AI Agent Development: design, build, deploy autonomous AI agents.
• LLM Integration: integrate LLMs into core products and services.
• MCP Implementation: connect AI models to data sources and tools.
• Automated Code Generation: build systems for code generation and testing.
• System Engineering: write scalable Java and Python for AI backend.
• Google Ecosystem Integration: use Google ADK and Vertex AI services.
• Cross-Functional Collaboration: work with product managers and data scientists.

Skills

Java

Python

Google AI Tools

LLMs

Agentic Workflows

MCP Protocol

Code Generation

Tools

Google ADK

Job description

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

Duration: 6+ Months

Job Summary:

We are seeking an innovative and highly skilled AI Engineer to join our dynamic team. The ideal candidate will bridge the gap between traditional software engineering and cutting-edge artificial intelligence. You will be instrumental in designing, building, and deploying advanced AI agents, working closely with Large Language Models (LLMs), and driving automated code generation initiatives. If you have a strong foundation in Java and Python, coupled with hands-on experience using Google's AI tools, we want you to help us build the next generation of intelligent applications

Key Responsibilities:

• 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.
• Google AI Tools: Hands‑on experience with Google ADK (or equivalent Google Cloud AI/Vertex AI tools).
• LLM Expertise: Deep comfort level and practical experience working with Large Language Models (prompt engineering, fine‑tuning, RAG architectures).
• Agentic Workflows: Demonstrable experience in building and orchestrating AI Agents (using frameworks like LangChain, LangGraph, or custom implementations).
• MCP Knowledge: Familiarity and practical experience with the Model Context Protocol (MCP) for standardizing AI interactions with external tools.
• Code Generation: Experience in leveraging AI tools or building pipelines specifically for code generation and software automation.