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# GenAI Engineer

- **Company:** Diverse Lynx LLC
- **Location:** Newark, NJ, United States
- **Experience:** Expert
- **Salary:** $130,000
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, Application Programming Interfaces (APIs), Artificial Intelligence, Microsoft Azure, Cloud Computing, Computer Programming, Databases, Language Modeling, Software Engineering, Enterprise Search, Pinecone, Enterprise Software Applications, Retrieval-Augmented Generation, Large Language Models, Prompt Engineering, Model Validation, Llamaindex, Generative AI, Agentic-AI, AI Platforms, AutoGen, FAISS, Claude, Google Gemini, Semantic Kernel, GPT, ChromaDB
- **Published:** November 6, 2026
- **Apply:** https://www.careerbuilder.com/job-details/genai-engineer-newark-nj--bdf65a9a-1180-47f3-9cdf-9142178b1c7d

## About the Role

Artificial Intelligence (AI), Kernel Programming, Microsoft Windows Azure, Production Systems, Software Engineering, Cloud Computing, Artificial Intelligence (AI) Agents, Modeling Languages, Use Cases, Business Case, * Primary: Artificial intelligence, LLM

 * Secondary: Retrieval-Augmented Generation (RAG), FAISS, ChromaDB, or Azure AI Search, LanEligible to workhain, LangGraph, LlamaIndex, AutoGen, or Semantic Kernel

Experience: 7 to 10 yrs

## Description

We are seeking an experienced Generative AI Engineer with proven expertise in designing, developing, deploying, and supporting AI solutions in production environments. The ideal candidate should have hands-on experience with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), prompt engineering, AI agents, vector databases, and cloud based AI platforms. The candidate should have successfully delivered enterprise-grade GenAI applications used by business users in production., * Design, develop, and deploy Generative AI solutions for enterprise business use cases.

 * Build and maintain production-ready applications utilizing LLMs such as GPT, Claude, Gemini, Llama, or similar models.
 * Develop RAG-based solutions using vector databases such as Pinecone, FAISS, ChromaDB, or Azure AI Search.
 * Implement prompt engineering, prompt tuning, and model evaluation frameworks.
 * Integrate AI applications with enterprise systems, APIs, databases, and cloud platforms.
 * Monitor production AI applications for performance, accuracy, latency, and cost Eligible to workimization.
 * Design AI agents and workflow automation using frameworks such as LanEligible to workhain, LangGraph, LlamaIndex, AutoGen, or Semantic Kernel.
 * Implement responsible AI controls, security, governance, and compliance requirements.
 * Collaborate with business stakeholders, architects, data scientists, and engineering teams to deliver scalable AI solutions.
 * Troubleshoot and resolve production issues related to AI systems.