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# Generative AI/LLM Engineer

- **Company:** Kforce Inc.
- **Location:** Frisco, TX, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Software Applications, Computer Vision, Microsoft Azure, Software as a Service, Continuous Integration, Software Design Patterns, Information Extraction, Python (Programming Language), Machine Learning, OpenAI, Next.js, Search Technologies, Software Deployment, Software Engineering, Systems Integration, Strategies of Testing, Speech Recognition, Pinecone, Google Cloud, Enterprise Software Applications, LangChain, ReactJS, Large Language Models, Prompt Engineering, Model Validation, Zapier, Llamaindex, Generative AI, Backend, Agentic-AI, Containerization, AI Platforms, Kubernetes, Information Technology, CrewAI, Weaviate, AutoGen, Milvus, Nintex, Machine Learning Operations, Speech Synthesis, Front End Software Development, Virtual Agents, Restful APIs, Docker, ChromaDB, Microservices
- **Published:** October 12, 2026
- **Apply:** https://www.dice.com/job-detail/a3846d02-a747-4de6-9677-acb7a02c4227

## About the Role

* Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Software Engineering, or a related technical field
 * 5+ years of professional software development experience, including significant Python development
 * Hands-on experience building solutions with leading LLM providers such as OpenAI, Anthropic, Meta, Mistral, or similar platforms
 * Strong understanding of prompt engineering, model evaluation, and AI application development
 * Experience designing and implementing Retrieval-Augmented Generation (RAG) architectures
 * Experience with vector databases and semantic search platforms such as Pinecone, Weaviate, Chroma, Milvus, or equivalent technologies
 * Experience building REST APIs, microservices, and scalable cloud-based applications
 * Knowledge of AI agent frameworks such as LangChain, LlamaIndex, CrewAI, AutoGen, or similar platforms
 * Experience deploying applications in AWS, Azure, or Google Cloud environments
 * Strong understanding of software design patterns, testing methodologies, and CI/CD practices
 * Excellent communication and collaboration skills in cross-functional environments, * Experience with speech technologies, including speech-to-text and text-to-speech solutions
 * Experience with image generation, computer vision, or multimodal AI applications
 * Knowledge of workflow automation tools such as n8n, Make, Zapier, or similar platforms
 * Experience with Docker, Kubernetes, and containerized deployments
 * MLOps experience supporting model deployment, monitoring, and continuous improvement
 * Familiarity with React, Next.js, or modern front-end frameworks
 * Experience building enterprise-scale AI products used by large internal or external audiences
 * Demonstrated success delivering AI solutions from concept through production deployment

## Description

Kforce has a client in Frisco, TX that is seeking an experienced Generative AI/LLM Engineer to design, build, and deploy enterprise-scale AI solutions that drive automation, improve user experiences, and accelerate business outcomes. This role will focus on developing intelligent agents, Retrieval-Augmented Generation (RAG) platforms, multimodal AI capabilities, and workflow automation solutions across a variety of business functions. The ideal candidate combines strong software engineering fundamentals with hands-on experience delivering production-ready AI systems. You will collaborate with cross-functional teams to identify opportunities, design scalable architectures, and implement AI-powered solutions that create measurable value., * Design, develop, and deploy AI agents powered by Large Language Models (LLMs)

 * Build and optimize Retrieval-Augmented Generation (RAG) solutions using vector search technologies and semantic retrieval
 * Develop AI-powered applications that leverage text, voice, image, and document intelligence
 * Build scalable APIs, microservices, and backend services supporting AI workloads
 * Create integrations between AI platforms, enterprise systems, and automation frameworks
 * Implement workflow automation and orchestration solutions to streamline business processes
 * Evaluate, monitor, and improve model accuracy, performance, reliability, and cost efficiency
 * Collaborate with product, engineering, operations, and business stakeholders to deliver AI initiatives
 * Apply prompt engineering best practices to improve outputs and user experiences
 * Ensure solutions meet security, privacy, governance, and responsible AI requirements
 * Contribute to architecture standards, reusable components, and AI engineering best practices
 * Stay current with emerging AI technologies and recommend innovative approaches for future adoption