Senior Trainer - Artificial Intelligence & Machine Learning (RAG, Agentic AI & Deployment)

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Revature · Remote_texas

Full-timeOn-siteToday

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About the role

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, and deploying top tech talent. Our mission is to create a pathway for candidates from diverse experiences and educational backgrounds to reach their potential as technology professionals. Alumni of the Revature program work on innovative, challenging, and rewarding software development projects across the United States. Revature has trained over 7000 software engineers across 54 technical disciplines,

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 .

Senior Trainer - Artificial Intelligence & Machine Learning (RAG, Agentic AI & Deployment)

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