Graph and Data Engineer

This is a fully remote position, open to applicants in United States, +4 more locations.

📋 Description

• Construct a canonical entity and knowledge graph through Intelligence Core connectors to resolve identities.

• Spearhead the classify-at-source pilot in collaboration with Finance and Compliance to create unified tagging models and metrics.

• Create shadow-AI and agent-identity registers that define ownership, access controls, and data permissions.

• Develop entity resolution pipelines across platforms like Slack, Jira, and Ironclad utilizing privacy-preserving linkage and canonical IDs.

• Create graph-based correlation capabilities and set baseline metrics for operational throughput and SAR false positives.

• Ground operational agents within a shared graph for cohesive event tracking, reasoning, and real-time authorization.

• Define the architecture of the graph, including schemas, temporal permissions, and provenance tracking.

• Ensure data accuracy through bitemporal modeling, automated drift detection, and historical replay.

• Model delegation chains and agent credentials anchored to human principals.

• Implement ML and graph-native approaches to analyze multi-agent behavior, detect anomalies, and identify shared lineage or prompts.

• Assess and incorporate emerging research in graph and identity-resolution.

• Uphold regulatory compliance, jurisdictional data partitioning, and standards of privacy-by-design.

⛳️ Requirements

• Proven experience with entity resolution, identity systems, or knowledge-graph modeling.

• Proficiency in Python along with graph or relational data engineering in a production environment.

• Experience applying ML for large-scale resolution, potentially including embedding- and LLM-based matching, self-supervised, and active-learning loops.

• Strong discipline to benchmark prior to trust, using synthetic or de-identified datasets, as raw PII should never be part of an evaluation.

• Expertise in schema and API design for diverse consumers, both human and machine.

• Willingness to work directly with Finance and Compliance teams on a live data pilot starting from the initial weeks.

• Commitment to security and privacy by design as a standard practice.

• Experience in designing an identity layer within an MSB/VASP environment.

• Comfort in developing a foundational layer for consumers that may not yet exist.

🏝️ Benefits

• Healthcare Insurance: zerohash covers approximately 100% of employee premiums, as well as a portion for spouses/children (U.S. only).

• Vision & Dental Insurance (U.S. only).

• Opportunity to earn equity.

• Maternity & Paternity leave (after 6 months).

• WeWork All Access Membership.

• WFH Yearly Stipend.

• L&D Yearly Stipend (after 6 months).