AI Engineer

Role

AI Engineer

Location

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

Rate

$60/hr. (do not exceed)

No of roles

2

Indent

PSL311992-3

Year of Experience

5+ yrs

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.

Good-to-Have (Optional but highly valued)

• Experience with modern robust backend frameworks (e.g., Spring Boot for Java, FastAPI for Python).
• Familiarity with containerization and orchestration (Docker, Kubernetes).

Experience with vector databases (e.g., Pinecone, Weaviate, Milvus