[Job - 32565] AI Engineer Senior, Brazil

Role overview Develop the graph data layer for an AI-powered style recommendation service focused on formal occasions. The work turns editorial content and product information into a structured knowledge graph that an AI agent can query, with ownership spanning schema design, data ingestion, entity matching, and query performance. You will work closely with machine learning and agent development colleagues in a client team.

Responsibilities - Design graph entities and relationships for products, designers, style attributes, trends, occasions, and editorial content. - Build batch ingestion processes that load structured data from upstream pipelines into the graph. - Match extracted product mentions to catalog items by scoring attribute similarity; set confidence thresholds and prevent duplicate entities across articles. - Weight graph relationships according to the prominence of an item or trend in its source content. - Write and tune multi-hop openCypher queries to return useful recommendation data within a three-second target. - Coordinate graph design with the recommendation and retrieval needs of the AI agent, and assist with technical validation of new team members when needed.

Requirements - Advanced English proficiency (C1 or higher) and confidence communicating directly with international stakeholders. - Solid experience with property graph modeling, schema trade-offs, and openCypher query optimization. - Experience building entity resolution logic, including fuzzy matching, scoring, and deduplication across sources. - Strong Python skills for data engineering and batch processing of structured payloads. - Ability to work independently in a fast-paced, client-integrated team.

Nice to have Experience with Amazon Neptune, fashion, retail or e-commerce catalogs, AWS databases or analytics certification, recommendation systems, content ranking, or connecting graph data to generative AI agents.