AI Engineer

Job description

A leading organization is seeking an AI Engineer to develop generative AI capabilities for a content recommendation and drafting solution. The AI Engineer will build systems that use historical human decisions to recommend relevant content, retrieve useful reference examples, and generate written outputs that align with established patterns and tone.

The position combines Large Language Model development, retrieval-augmented generation (RAG), semantic search, prompt engineering, and AI evaluation. The AI Engineer will also partner with data engineering and business stakeholders to improve output quality through testing and human feedback.

Responsibilities

• Design AI-powered recommendation capabilities using historical labeled data and human decisions.
• Develop RAG workflows that retrieve relevant historical examples to inform generated content.
• Build and refine prompts for LLM-based summarization and content generation.
• Use embeddings, vector search, and semantic similarity techniques to identify relevant reference content.
• Develop approaches for adjusting generated outputs based on context and desired tone.
• Evaluate AI recommendations and generated content against historical examples and established quality expectations.
• Help define measurable criteria for assessing LLM output quality and recommendation performance.
• Identify cases with insufficient or conflicting source information and route them for additional human review.
• Evaluate whether available historical data provides sufficient context for less frequently occurring topics.
• Partner with data engineering resources on data structures, metadata, and labeling requirements.
• Refine AI outputs based on pilot results and stakeholder feedback.
• Use SQL to independently analyze labeled data, metadata, and audit information.
• Use Python to support AI development, experimentation, and solution delivery.

Required experience and skills

• Hands-on experience with Large Language Models, prompt engineering, and retrieval-augmented generation.
• Strong SQL skills for independently querying labeled datasets, metadata, and audit records.
• Python development skills and experience using AI-assisted coding tools.
• Experience with embeddings, vector search, and semantic similarity techniques such as cosine similarity.
• Experience evaluating LLM-generated outputs against reference examples or established quality criteria.
• Experience working with Google Cloud Platform technologies for AI development.
• Experience with generative AI services, model development platforms, semantic search, or vector indexing.
• Experience with content ranking or recommendation systems using labeled human decisions is preferred.
• Experience designing or supporting human-in-the-loop AI review workflows is preferred.
• Experience with Python application frameworks is preferred.
• Familiarity with relational databases such as PostgreSQL is preferred.