AI/ML Lead - Dallas TX/Tampa FL (Full Time Only)

Job Description:

We are seeking an experienced Senior Generative AI Developer to design and implement cutting-edge AI solutions leveraging Retrieval-Augmented Generation (RAG) techniques. The ideal candidate will have strong expertise in Python programming, FastAPI, and cloud platforms (AWS, Azure, or GCP). This role requires a deep understanding of system architecture design, scalable APIs, and end-to-end AI solution development

.
Key Responsibilitie

• s:
  Architect and develop Generative AI applications using RAG frameworks for enterprise-scale solutio
• ns.Design and implement robust system architectures for AI-driven platforms ensuring scalability, security, and performan
• ce.Build and optimize APIs using FastAPI for seamless integration with AI models and data pipelin
• es.Collaborate with cross-functional teams to integrate AI solutions into existing systems and workflo
• ws.Implement data ingestion, preprocessing, and retrieval mechanisms for large-scale knowledge bas
• es.Ensure compliance with best practices for cloud deployment (AWS, Azure, or GC
• P).Conduct performance tuning and optimization of AI models and AP
• Is.Stay updated with the latest advancements in Generative AI, LLMs, and RAG methodologi

es.
Required Skills & Qualificat

• ions
  8+ years of professional experience in software development and system de
• sign.Strong proficiency in Python and experience with FastAPI for API develop
• ment.Hands-on experience with Generative AI frameworks and RAG architect
• ures.Solid understanding of system and architecture design principles for distributed applicat
• ions.Experience deploying solutions on any major cloud platform (AWS, Azure,
• GCP).Familiarity with vector databases, embedding models, and retrieval pipel
• ines.Strong problem-solving skills and ability to work in a fast-paced environ

ment.
Preferred Qualific

• ations
  Experience with LLM fine-tuning, prompt engineering, and model eval
• uation.Knowledge of containerization (Docker) and orchestration (Kuber
• netes).Exposure to CI/CD pipelines and DevOps pra