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# Senior GenAI Engineer

- **Company:** Raas Infotek LLC
- **Location:** Illinois City, IL, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Cloud Engineering, Distributed Systems, Graph Database, Python (Programming Language), Performance Tuning, Search Technologies, Software Engineering, Systems Integration, AI Infrastructure, Google Cloud, Enterprise Software Applications, Chatbots, LangChain, Retrieval-Augmented Generation, Open-source Models, Large Language Models, Multi-Agent Systems, Prompt Engineering, Llamaindex, Generative AI, Agentic-AI, Fastapi, Information Technology, CrewAI, AutoGen, Machine Learning Operations, Claude, Evaluation of Large Language Models, Google Gemini, Graph RAG, Restful APIs, Model Context Protocol, GPT, Docker, Microservices
- **Published:** October 16, 2026
- **Apply:** https://www.dice.com/job-detail/dc2dbead-a1a7-458d-ada0-7f87863d2347

## About the Role

We are seeking a highly experienced Senior Generative AI Engineer with 10+ years of overall IT experience and strong hands-on expertise in developing, deploying, and scaling enterprise-grade Generative AI and Agentic AI solutions.

The ideal candidate should have extensive experience with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Python, AI agents, cloud platforms, and MLOps., * 10+ years of overall IT/software engineering experience.

 * 3+ years of hands-on AI/ML or Generative AI experience, including production GenAI implementations.
 * Strong Python development experience.
 * Proven experience building production-ready LLM and RAG applications.
 * Hands-on experience with Agentic AI frameworks such as LangGraph, CrewAI, or AutoGen.
 * Experience integrating vector databases and enterprise data sources.
 * Strong understanding of cloud-native architecture and microservices.
 * Experience deploying AI applications using Docker and Kubernetes.
 * Knowledge of LLM evaluation, observability, security, and performance optimization.
 * Excellent communication, problem-solving, and technical leadership skills., * Experience designing enterprise-scale Agentic AI solutions.
 * Knowledge of Model Context Protocol (MCP).
 * Experience with multimodal AI (text, image, audio, and video).
 * Experience implementing AI governance and responsible AI frameworks.
 * Knowledge of advanced RAG architectures, GraphRAG, and knowledge graphs.
 * Experience with distributed systems and high-performance AI infrastructure.

## Description

* Design, develop, and deploy enterprise-grade Generative AI and Agentic AI applications.
 * Build and optimize LLM-powered applications using GPT, Claude, Gemini, Llama, and other open-source models.
 * Develop advanced RAG pipelines using LangChain, LlamaIndex, and vector databases.
 * Implement multi-agent AI systems using LangGraph, CrewAI, and AutoGen.
 * Develop AI-powered chatbots, virtual assistants, and intelligent automation solutions.
 * Integrate LLMs with enterprise applications using REST APIs, FastAPI, and microservices.
 * Implement prompt engineering, fine-tuning, embeddings, and semantic search techniques.
 * Design and deploy scalable AI solutions on AWS, Azure, or Google Cloud.
 * Build CI/CD pipelines and implement LLMOps/MLOps best practices.
 * Optimize LLM performance, latency, token consumption, and operational costs.
 * Implement AI security, governance, guardrails, and responsible AI practices.
 * Collaborate with architects, data scientists, product managers, and business stakeholders.