"Artificial intelligence, especially Generative AI and large language models, is reshaping every industry, making Python expertise more valuable than ever. Companies are racing to deploy intelligent solutions, and a contract role in Tampa offers hands\u2011on experience with cutting\u2011edge models. This position gives you the chance to blend Python, Node.js, and MLOps skills while working directly with cloud platforms.\n\n# Job Summary\nWe are seeking a contract Python Developer with strong Node.js knowledge to design, develop, and deploy AI/ML pipelines. The role focuses on building generative AI solutions, fine\u2011tuning LLMs, and implementing MLOps practices on AWS/Azure/GCP for a 12\u2011month onsite engagement in Tampa, FL.\n\n# Top 3 Critical Skills Table\n| Skill | Why it's critical | Mastery Level |\n|-------|-------------------|---------------|\n| Python (expert) | Core language for model development and data pipelines | Senior |\n| Generative AI & LLMs | Drives the primary product functionality and innovation | Senior |\n| MLOps & Cloud (AWS/Azure/GCP) | Ensures scalable, reliable deployment of AI models | Senior |\n\n# Interview Preparation\n1. **Explain how you would fine\u2011tune a pre\u2011trained LLM using PyTorch.** \n *What the interviewer is looking for:* Understanding of model loading, optimizer setup, dataset preparation, and training loops.\n\n2. **Describe the steps to implement Retrieval\u2011Augmented Generation (RAG) in a production system.** \n *What the interviewer is looking for:* Knowledge of vector stores, query embedding, document retrieval, and prompt construction.\n\n3. **How do you containerize a Python ML pipeline for deployment on AWS SageMaker?** \n *What the interviewer is looking for:* Experience with Docker, SageMaker SDK, entry\u2011point scripts, and resource configuration.\n\n4. **What are the trade\u2011offs between using SQL vs. NoSQL for storing feature data?** \n *What the interviewer is looking for:* Ability to discuss consistency, scalability, query patterns, and latency considerations.\n\n5. **Walk me through a prompt\u2011engineering strategy to improve LLM output quality.** \n *What the interviewer is looking for:* Insight into prompt design, few\u2011shot examples, temperature tuning, and iterative testing.\n\n# Resume Optimization\n- Python\n- Node.js\n- PyTorch\n- TensorFlow\n- Generative AI\n- Large Language Models\n- MLOps\n- AWS\n- Azure\n- Prompt Engineering\n\n# Application Strategy\nWhen emailing the recruiter, start with a brief greeting, attach your updated resume, and clearly highlight your top relevant skills. Make sure to mention related skills you possess, such as Python expertise, Generative AI experience, and MLOps proficiency, and reference specific projects where you applied these technologies.\n\n# Career Roadmap\n| Current Role | Typical Experience | Core Focus | Next Position |\n|--------------|-------------------|------------|---------------|\n| Contract Python Developer | 1\u20132 years AI/ML projects | Model development, MLOps | Senior AI Engineer |\n| Senior AI Engineer | 3\u20135 years end\u2011to\u2011end solutions | Architecture, leadership | Lead ML Engineer |\n| Lead ML Engineer | 5+ years strategic AI initiatives | Team management, roadmap | Director of AI/ML |"