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Join a Series A–funded digital asset risk-management platform backed by Microsoft, Coinbase, Samsung, Nyca, and Neotribe. With $22M raised and three years of financial runway, the company powers real-time risk monitoring, analytics, and intelligence insights for financial institutions, custodians, tokenized-asset issuers, and regulators. Their mission is to enable safe, compliant, scalable blockchain participation for institutions on a global scale. As VP of Engineering, you will lead and scale the engineering organization responsible for delivering the company’s core risk platform. You’ll define technical direction across architecture, data infrastructure, analytics systems, and compute pipelines, while integrating emerging intelligence-driven capabilities such as automated risk scoring, alerting, reporting, and anomaly detection. You’ll work cross-functionally with Product, Analytics, and Customer Success, operating as a technical and strategic leader shaping the next phase of platform evolution.
Job Responsibility:
Engineering Leadership & Execution: Lead engineering teams across backend, frontend, SRE, data platforms, and risk analytics
Drive execution of the engineering roadmap, delivering secure, scalable enterprise software
Define engineering processes that promote iteration, performance, and predictable delivery in a remote-first environment
Architecture & Platform Direction: Own end-to-end evolution of platform architecture: ingestion pipelines, scoring engines, real-time compute, APIs, and integrations
Guide system design decisions that ensure resilience, scale, and extensibility amid growing regulatory and market complexity
Lead technical direction for enterprise deployments, POCs, and customer integrations
Data Infrastructure & Analytics: Scale the data platform to support broader asset coverage, higher throughput, and more sophisticated analysis
Develop advanced analytics capabilities including anomaly detection, cross-chain signals, and automated scoring models
Ensure data accuracy, quality, and resiliency across pipelines and computation layers
Emerging AI & Automation Capabilities: Introduce new automation, reporting, and workflow intelligence features
Integrate AI-powered classification, alerting, risk scoring, and customer-facing insights securely and transparently
Ensure future enhancements remain enterprise-ready, explainable, and compliant
Cross-Functional Collaboration: Work with Product and Analytics to convert customer needs into technical execution plans
Support Sales Engineering and BD by communicating technical capabilities and roadmap direction
Serve as a technical leader in customer evaluations, deployments, and audits
Requirements:
Languages & Backend: Python, Go (Golang), TypeScript
Strong understanding of distributed systems, microservices, API-driven architectures
Data & Analytics: AWS Redshift, Athena, DynamoDB, Snowflake (or equivalent cloud data warehouses)
Kafka, Kinesis, or other streaming/event platforms
Experience building large-scale ingestion and normalisation pipelines
Experience with analytics engines, scoring frameworks, and real-time compute
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