GenAI / LLM / RAG Developer / Architect - Dallas TX (Onsite)

GenAI / LLM / RAG Developer / Architect - Dallas TX (Onsite)

***2 positions Filled 1 1 more to fill ***

Location: Dallas, TX (Onsite)

Duration: Contract

Employment Type: W2 / C2C

Job Summary

We are seeking a highly skilled GenAI / LLM Developer with strong expertise in Python, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG) to design and build scalable AI-powered applications. The ideal candidate will have hands-on experience implementing enterprise-grade generative AI solutions and integrating LLMs into real-world business workflows.

This role requires strong technical depth in modern AI frameworks, API integrations, and production deployment practices.

Key Responsibilities

• Design, develop, and deploy Generative AI applications using LLMs.
• Build and optimize RAG pipelines integrating vector databases and document retrieval systems.
• Develop backend services and APIs using Python (FastAPI / Flask).
• Integrate OpenAI, Azure OpenAI, Anthropic, or open-source LLMs (Llama, Mistral, etc.).
• Implement prompt engineering, fine-tuning, and model optimization strategies.
• Work with embeddings, semantic search, and vector stores (Pinecone, FAISS, Weaviate, Chroma, etc.).
• Develop scalable data pipelines to process structured and unstructured data.
• Ensure performance optimization, security, and responsible AI practices.
• Collaborate with data engineers, ML engineers, and product teams.

Required Skills

• 8+ years of software development experience.
• Strong proficiency in Python.
• Hands-on experience with:
• Large Language Models (LLMs)
• Retrieval-Augmented Generation (RAG)
• Prompt engineering
• Embeddings and vector databases
• Experience with AI/ML frameworks (LangChain, LlamaIndex, HuggingFace, etc.).
• Experience building REST APIs.
• Knowledge of cloud platforms (AWS, Azure, or Google Cloud Platform).
• Familiarity with Docker / CI-CD pipelines.

Preferred Qualifications

• Experience with Azure OpenAI or enterprise AI governance.
• Knowledge of fine-tuning and model evaluation.
• Experience in production deployment of AI systems.
• Background in data engineering or ML Ops.
• Experience working in enterprise or consulting environments.

Nice to Have

• Frontend integration experience (React or similar).
• Experience with knowledge graphs.
• Understanding of AI compliance and security standards.