Senior Trainer – Artificial Intelligence & Machine Learning (RAG, Agentic AI & D

Revature is rapidly growing – both domestically and internationally – and our Team plays a key role in our Corporate Department. We’re looking for an agile and ambitious candidate who is effective in the qualities listed below, all within a rapidly growing environment. Our ideal candidate is based near one of our central offices located in this job posting. Job Description: Experience Required: Minimum 4-5 years of professional experience in AI/ML, Data Science, or Applied Machine Learning. Position Summary: We are seeking a passionate and technically strong Senior Trainer - Artificial Intelligence & Machine Learning to deliver our advanced AI curriculum focused on LLMs, Retrieval-Augmented Generation (RAG), Agentic AI, and end-to-end deployment. The ideal candidate will have a deep understanding of modern AI architectures and the ability to mentor learners in building autonomous, production-grade AI systems - integrating retrieval pipelines, intelligent agents, and deployment workflows across real-world scenarios. Key Responsibilities • Deliver engaging, project-based sessions on advanced topics in AI, LLMs, and agentic AI development. • Train and mentor learners on: • Core AI/ML concepts: supervised & unsupervised learning, deep learning, and NLP. • Large Language Models (LLMs): transformer architecture, fine-tuning, and prompt optimization • Retrieval-Augmented Generation (RAG): vector databases, document retrieval, embeddings, and knowledge-grounded responses. • Agentic AI Systems: • Designing and orchestrating AI agents capable of autonomous decision-making • Using LangGraph, CrewAI, or AutoGen for multi-agent frameworks • Integrating external tools, APIs, and reasoning loops for dynamic task execution • Understanding memory management, context persistence, and tool use in agent frameworks • AI Deployment & MLOps: • Building scalable APIs with FastAPI or Flask • Model packaging and orchestration with Docker, Kubernetes, and CI/CD pipelines • Model tracking, experimentation, and monitoring with MLflow, Weights & Biases, or Vertex AI Pipelines. • Cloud AI Integration: deploying and managing systems on AWS (SageMaker), Azure ML, or GCP Vertex AI. • Lead hands-on projects where learners build RAG-based chatbots, autonomous AI assistants, and deployed LLM applications. • Collaborate on curriculum development to integrate cutting-edge AI research and tools into the training modules. • Mentor learners through technical challenges, performance optimization, and model deployment. • Keep up to date with LLM, agentic AI, and generative AI innovations to ensure curriculum relevance. Required Skills & Qualifications • Experience: 4 to 5+ years in AI/ML engineering, Data Science, Applied NLP, or MLOps roles. • Technical Expertise: • Proficiency in Python and AI libraries such as PyTorch, TensorFlow, and Transformers (Hugging Face). • Strong experience with LLMs, prompt engineering, and fine-tuning. • Practical understanding of RAG systems using LangChain and vector databases (e.g., FAISS, Chroma, Pinecone). • Hands-on experience in agentic AI frameworks (e.g., CrewAI, AutoGen, LangGraph, or LangChain Agents). • Knowledge of tool integration, memory management, and multi-agent orchestration. • Experience deploying AI models with FastAPI, Docker, Kubernetes, or cloud-native tools. • Familiarity with MLOps pipelines, CI/CD automation, and monitoring frameworks. • Exposure to Generative AI APIs such as OpenAI, Anthropic Claude, Google Gemini, or Azure OpenAI. • Education: Bachelor’s or Master’s degree in Computer Science, Data Science, or Artificial Intelligence or similar technical discipline. • Excellent communication, mentoring, and technical training skills. • Proven experience conducting technical workshops, bootcamps, or corporate AI training programs preferred. • Ready to deliver on-site and virtual training. Preferred Skills/Attributes • Certifications in Machine Learning, Generative AI, or Cloud AI services. • Experience developing autonomous AI agents and multi-agent ecosystems. • Working knowledge of vector search optimization, knowledge graph integration, and RAG performance tuning. • Understanding of AI ethics, bias mitigation, and responsible AI deployment. • Enthusiasm for teaching and guiding professionals through hands-on AI and MLOps implementations. Who We Are Revature is a tech career launch pad and the largest employer of entry-level technology talent in the U.S. The company works with Fortune 500 companies, government organizations, and top systems integrators to grow their business by hiring, training, a