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