AI Senior Engineer (Graph)

What you’ll be doing

We are seeking someone who views the Knowledge Graph not just as a database, but as a living organism that requires constant care, feeding, and pruning. You understand that a RAG system is only as good as the data underlying it. You are intrigued by the complexity of ingesting massive, messy datasets and transforming them into clean, connected knowledge.

In short, someone who likes:

• Architecting Graph ETL: Designing and developing robust ETL pipelines specifically for graph ingestion. You aren't just dumping rows into tables; you are determining how disparate data sources connect, evolve, and relate in a graph structure.
• Data Ingestion at Scale: Managing high-volume data streams using tools like Kafka and implementing CDC (Change Data Capture) patterns to ensure the graph reflects real-time reality.
• Automated Graph Hygiene: Writing scripts and jobs for deduplication, orphan node detection, and data consistency checks. You take pride in a clean schema.
• Modeling Time: Handling complex temporal relationships (e.g., how property ownership or financial status changes over time) within the graph.
• Performance Tuning: Ensuring that as the graph grows (25k+ reports and beyond), the underlying query performance remains snappy through optimizing indexes and storage.

What we’re looking for

We want to work with people who have a passion for collaborating with their teams, building software while nurturing inclusive and respectful relationships with their coworkers. With the ones that are open about their shortcomings and what they do not know now, but remain eager to keep on growing and closing those gaps.

Ideally, they would also have:

• Neo4j Expertise (Must Have): 4+ years of hands-on experience. You master Cypher, schema design, and the operational side of managing a production graph.
• ETL & Pipeline Mastery: Strong background in building data pipelines. You know how to take raw data, clean it, and structure it for graph ingestion.
• Streaming & CDC: Familiarity with event streaming platforms like Kafka and Change Data Capture methodologies to sync operational databases with the graph.
• Python Proficiency: Strong Python skills for writing ingestion scripts, maintenance jobs, and custom graph algorithms.
• Data Integrity Focus: Experience implementing automated jobs for entity resolution, deduplication, and quality assurance.