GenAI Engineer
US client via staffing partner · Dallas, TX or Charlotte, NC
- Location
- Dallas, TX or Charlotte, NC · Onsite
- Salary band
- Band not stated
- Type
- Full-time
- Level
- Senior
- Work authorization
- Not stated
Stack
Python · LLMs · RAG · LangChain · LangGraph · LlamaIndex · OpenAI · Azure OpenAI · Anthropic Claude · Google Gemini · Prompt Engineering · Vector Databases · REST APIs · AWS · Microsoft Azure · Google Cloud Platform · Git · CI/CD · Docker · Kubernetes
About the role
GenAI Engineer Experience: 7+ Years Employment Type: Full-Time Location: Dallas, TX or Charlotte, NC Job Description We are seeking an experienced GenAI Engineer to design, develop, and implement Generative AI solutions using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and AI application development frameworks. The ideal candidate will have strong software engineering skills and experience building scalable, secure, and production-ready AI applications. Key Responsibilities - Design, develop, and deploy Generative AI applications using LLMs and modern AI frameworks. - Build and implement RAG-based solutions using document ingestion, embeddings, vector databases, and semantic search. - Develop and optimize prompts to improve the accuracy, relevance, and reliability of LLM responses. - Work with LLMs such as OpenAI, Azure OpenAI, Anthropic Claude, Google Gemini, and open-source models. - Develop AI-powered applications, chatbots, intelligent assistants, and enterprise automation solutions. - Use frameworks such as LangChain, LangGraph, LlamaIndex, or similar tools for LLM application development and orchestration. - Integrate AI solutions with enterprise applications, REST APIs, databases, and external services. - Implement evaluation, monitoring, guardrails, security, and responsible AI practices. - Optimize model performance, response quality, latency, and cost. - Collaborate with product managers, architects, data engineers, and development teams to translate business requirements into AI solutions. - Follow software engineering best practices, including version control, automated testing, CI/CD, and production deployment. - Support troubleshooting, continuous improvement, and maintenance of deployed AI applications. Required Skills and Qualifications - 7+ years of software development, engineering, or related technical experience. - Strong programming experience in Python. - Hands-on experience developing Generative AI applications using LLMs. - Strong understanding of RAG architecture, embeddings, vector databases, and semantic search. - Experience with prompt engineering, context management, and LLM response optimization. - Experience with frameworks such as LangChain, LangGraph, or LlamaIndex. - Experience integrating AI models with REST APIs, databases, and enterprise systems. - Understanding of LLM evaluation, hallucination mitigation, AI safety, and guardrails. - Experience with cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform. - Knowledge of Git, CI/CD, automated testing, and application deployment. - Strong analytical, problem-solving, communication, and collaboration skills. Preferred Qualifications - Experience with agentic AI, AI agents, tool calling, and multi-agent orchestration. - Experience with fine-tuning, model adaptation, or open-source LLMs. - Familiarity with vector databases such as Pinecone, Weaviate, Milvus, or FAISS. - Experience with Docker, Kubernetes, and scalable AI application deployment. - Knowledge of MLOps/LLMOps, model monitoring, and AI application observability. - Experience implementing enterprise-grade AI solutions with appropriate security and governance controls.
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