Lead AI Engineer

We are seeking an AI/ML Consultant to sit at the heart of our AI agent pipeline. The consultant will design and implement the core AI/ML components powering the event data extraction agent, including the RAG-based conversational assistant (UC2) and the reporting/analytics engine (UC3). The work spans LLM orchestration on Amazon Bedrock, knowledge base design, NLP pipelines and integration testing across the full agentic workflow. Responsibilities Design and build the RAG (Retrieval-Augmented Generation) pipeline for UC2 — a conversational agent surfacing approved training content in the flow of work Develop UC3 analytics support — reporting and insights generation from event data Configure and fine-tune LLM inference on Amazon Bedrock (LLM Backbone) Build Natural Language Processing pipelines for parsing event input from File, Text and Voice modalities Design knowledge base architecture (vector storage, chunking strategy, retrieval optimization) Lead integration testing across the AI agent and downstream CRM output Collaborate with a Data Analytics consultant on ETL pipelines feeding the AI models Support HITL (Human-in-the-Loop) validation checkpoints for AI-generated outputs Requirements Expertise in Amazon Bedrock, including LLM model selection, configuration and prompt engineering Proficiency in RAG architecture, covering vector databases, knowledge base design, embedding models and chunking strategies Skills in Natural Language Processing (NLP) such as entity extraction, classification and summarization Background in Python as the primary development language for ML pipelines Knowledge of AWS Lambda and Amazon S3 for serverless ML inference, event processing and data storage of training content and knowledge base artifacts Capability to perform integration testing for multi-step AI agent workflows Familiarity with Veeva CRM data schemas Upper-Intermediate English language proficiency (B2) Nice to have Flexibility to use MLflow or SageMaker for experiment tracking and model versioning Experience with voice-to-text processing pipelines AWS Certified Machine Learning – Specialty