{"schemaVersion":"jobsearcher.job.v1","id":"1841cbbd2c3ee7329fcdfbfc","url":"https://jobsearcher.com/jobs/1841cbbd2c3ee7329fcdfbfc","canonicalUrl":"https://jobsearcher.com/jobs/1841cbbd2c3ee7329fcdfbfc","title":"Graph and Data Engineer","description":"OverviewIn this role you will design and operate a canonical identity and knowledge graph across enterprise connectors to support automated system-level identity, authority, and permissions. You will build and govern an auditable, privacy-conscious entity layer that underpins security, compliance, and external interoperability. You will work closely with Finance and Compliance to pilot unified tag models, and you will apply ML and graph methods to monitor multi-agent behavior and detect anomalies. This position offers scope to shape core data governance and real-time authorization at scale within a regulated crypto infrastructure context.Compensation / BenefitsHealthcare Insurance: zerohash covers roughly 100% of employee premiums as well as a portion of spouse/children (U.S. only)Vision & Dental Insurance (U.S. only)Chance to earn equityMaternity & Paternity leave (after 6 months)WeWork All Access MembershipWFH Yearly StipendResponsibilitiesLead the classify-at-source pilot with Finance and Compliance to establish unified tag models and metricsEstablish shadow-AI and agent-identity registers to define ownership, access controls, and data permissionsBuild entity resolution pipelines across internal systems (Slack, Jira, Ironclad) using privacy-preserving linkage and canonical IDsDevelop graph-based correlation capabilities and establish verifiable baseline metrics for throughput and SAR false positivesGround operational agents in the shared graph to deliver unified event tracking, reasoning, and real-time authorizationDefine graph architecture, governing schemas, temporal permissions, and provenance tracking for full auditability and agent compatibilityMaintain data accuracy with bitemporal modeling, drift detection, and historical replay for complianceModel delegation chains and agent credentials anchored to human principals for secure external interoperabilityDeploy ML and graph-native methods to analyze multi-agent behaviors, detect anomalies, and identify shared lineage or promptsEvaluate and integrate emerging graph and identity resolution researchEnforce regulatory compliance, jurisdictional data partitioning, and privacy-by-design across the identity layerKey requirementsDirect experience with entity resolution, identity systems or knowledge-graph modellingStrong Python plus graph or relational data engineering in productionApplied ML for resolution at scale, including embedding- and LLM-based matching with benchmarking on synthetic/de-identified dataSchema and API design for heterogeneous consumers (human and machine)Comfort working with Finance and Compliance on live data pilotsSecurity and privacy by design mindset in regulated environmentsAbility to build foundational layers for future consumer usecollaborativeinitiativeproblem-solvingPythongraph/data engineeringML for resolution at scale","company":"Zero Hash","rawCompany":"zero hash","city":"Buffalo","state":"NY","isRemote":false,"isActive":false,"createdAt":"2026-10-26T13:38:35.241Z","occupations":[{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Graph and Data Engineer","description":"OverviewIn this role you will design and operate a canonical identity and knowledge graph across enterprise connectors to support automated system-level identity, authority, and permissions. You will build and govern an auditable, privacy-conscious entity layer that underpins security, compliance, and external interoperability. You will work closely with Finance and Compliance to pilot unified tag models, and you will apply ML and graph methods to monitor multi-agent behavior and detect anomalies. This position offers scope to shape core data governance and real-time authorization at scale within a regulated crypto infrastructure context.Compensation / BenefitsHealthcare Insurance: zerohash covers roughly 100% of employee premiums as well as a portion of spouse/children (U.S. only)Vision & Dental Insurance (U.S. only)Chance to earn equityMaternity & Paternity leave (after 6 months)WeWork All Access MembershipWFH Yearly StipendResponsibilitiesLead the classify-at-source pilot with Finance and Compliance to establish unified tag models and metricsEstablish shadow-AI and agent-identity registers to define ownership, access controls, and data permissionsBuild entity resolution pipelines across internal systems (Slack, Jira, Ironclad) using privacy-preserving linkage and canonical IDsDevelop graph-based correlation capabilities and establish verifiable baseline metrics for throughput and SAR false positivesGround operational agents in the shared graph to deliver unified event tracking, reasoning, and real-time authorizationDefine graph architecture, governing schemas, temporal permissions, and provenance tracking for full auditability and agent compatibilityMaintain data accuracy with bitemporal modeling, drift detection, and historical replay for complianceModel delegation chains and agent credentials anchored to human principals for secure external interoperabilityDeploy ML and graph-native methods to analyze multi-agent behaviors, detect anomalies, and identify shared lineage or promptsEvaluate and integrate emerging graph and identity resolution researchEnforce regulatory compliance, jurisdictional data partitioning, and privacy-by-design across the identity layerKey requirementsDirect experience with entity resolution, identity systems or knowledge-graph modellingStrong Python plus graph or relational data engineering in productionApplied ML for resolution at scale, including embedding- and LLM-based matching with benchmarking on synthetic/de-identified dataSchema and API design for heterogeneous consumers (human and machine)Comfort working with Finance and Compliance on live data pilotsSecurity and privacy by design mindset in regulated environmentsAbility to build foundational layers for future consumer usecollaborativeinitiativeproblem-solvingPythongraph/data engineeringML for resolution at scale","datePosted":"2026-10-26T13:38:35.241Z","dateModified":"2026-10-26T13:38:35.241Z","hiringOrganization":{"@type":"Organization","name":"Zero Hash","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Buffalo","addressRegion":"NY","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"1841cbbd2c3ee7329fcdfbfc"},"url":"https://jobsearcher.com/jobs/1841cbbd2c3ee7329fcdfbfc"}}