AI Senior Engineer (Graph)

Role overview A 100% remote LatAm position is open for a senior engineer who treats the knowledge graph as a living system that needs constant care, not just a database to query. The role focuses on ingesting messy, high-volume datasets and turning them into clean, connected knowledge that underpins retrieval-augmented generation. Success means keeping the graph accurate, current, and fast even as it scales into tens of thousands of reports.

Responsibilities - Architect ETL pipelines purpose-built for graph ingestion, deciding how disparate sources connect and evolve. - Manage high-volume data streams with tools such as Kafka and apply Change Data Capture patterns to keep the graph aligned with operational systems. - Write automated jobs for deduplication, orphan-node detection, schema hygiene, and data consistency checks. - Model temporal relationships that capture how entities change over time, such as property ownership or financial status. - Tune indexes, storage, and queries so performance holds steady as the graph grows beyond 25k reports.

Requirements - 4+ years of hands-on Neo4j experience, including Cypher, schema design, and production operations. - Strong background building data pipelines that clean and structure raw data for graph ingestion. - Familiarity with event streaming platforms like Kafka and CDC methodologies. - Solid Python skills for ingestion scripts, maintenance jobs, and custom graph algorithms. - Experience implementing entity resolution, deduplication, and quality assurance automation. - Excellent verbal and written English communication.

Nice to have - Ability to read or contribute to C# codebases. - Prior work in finance or real estate sectors.

Benefits and work setup - Fully remote across LatAm. - 40 hours per week during normal business hours. - Compensation paid in USD. - 18 days of paid time off per year, observance of local holidays, and a year-end break. - Wellness and remote stipends plus an AI learning voucher.