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# GEN AI Engineer

- **Company:** Propertyvalue Quantum Technologies Llc
- **Location:** Charlotte, NC, United States
- **Experience:** Expert
- **Salary:** $180,960.0
- **Contract:** Temporary contract
- **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, BigQuery, Databases, Distributed Systems, Python (Programming Language), Software Engineering, Systems Integration, Data Logging, Google Cloud, Large Language Models, Spring-boot, Generative AI, Backend, Google Cloud Functions, Restful APIs, Microservices
- **Published:** August 14, 2026
- **Apply:** https://www.dice.com/job-detail/32e3c5ae-3336-4cc5-849a-501c530e60a8

## About the Role

* 3 7 years of software development experience
 * Strong hands on experience in Python
 * 2+ years experience building and deploying real world agents in Production environment
 * Strong hands-on experience in Java backend development (4+ years exp)
 * Hands of experience in developing AI/ML or Generative AI projects
 * Core Technical Skills
 * Hands on experience on Google ADK, MCP servers, agent to agent communication, agent orchestration.
 * Java (4+), Spring Boot, Microservices
 * REST APIs and distributed systems design
 * Hands on experience on Python, LLMs, GenAI, and agent-based systems
 * Hands on experience with Google Cloud Platform services (Vertex AI preferred)

## Description

* Design and develop LLM-based AI agents capable of reasoning, planning, and task execution
 * Build and manage multi-agent orchestration workflows
 * Enable agents to interact with enterprise systems (APIs, databases, tools)
 * Java & Backend Engineering
 * Develop scalable backend applications using Java, Spring Boot, and Microservices
 * Build REST APIs to support AI-driven workflows and integrations
 * Ensure performance, scalability, and maintainability of services
 * Google Cloud Platform & GenAI Implementation
 * Develop AI solutions using Vertex AI, Gemini, BigQuery, Cloud Run, and Pub/Sub
 * Work with Vertex AI Agent Builder and Google ADK for agent development
 * LLM, RAG & Context Engineering
 * Implement Retrieval-Augmented Generation (RAG) pipelines
 * Build context-aware systems using vector search and embeddings
 * Optimize prompts and workflows for performance and cost
 * MLOps & Deployment
 * Deploy and monitor AI models and agents in production
 * Implement CI/CD pipelines, logging, and observability
 * Ensure reliability, safety, and guardrails for AI systems


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