Senior Director of Software Engineering - Margin and Collateral / Post Trade Technology

Key responsibilities: Engineering leadership & hands-on delivery Own the product/technology roadmap for both prime & clearing businesses encompassing both functional and non-functional deliveries. Lead platform architecture and implementation; remain close to the code/design (reviews, critical-path implementation, performance tuning). Drive engineering standards: CI/CD, test automation, release governance, coding standards, and secure engineering practices. Build and mentor a high-performing team of engineers and engineering managers. Margin methodologies & risk engine capability Own implementation and ongoing enhancement of margin methodologies including: Cleared/CCP : SPAN, TIMS (and related scenario/sensitivity and add-on logic, where applicable). Prime/Broker-dealer : FINRA Portfolio Margin, FINRA Rule 4210 , Regulation T , SEC 15c3-1 and related house margin overlays. Translate model/rule requirements into deterministic, testable, and explainable calculation services, with full audit trails and reproducibility. Partner with Risk Methodology teams on model governance, parameter/version controls, validation evidence, and change approvals. Intraday processing, scale, and resiliency Deliver real-time/intraday margining (e.g., trade/position events, market moves, concentration, scenario re-runs), and end-of-day cycles. Own non-functional outcomes: latency, throughput, scalability, availability, failover/DR readiness, and capacity planning. Establish SLOs/SLAs and observability (metrics, tracing, logging), and lead incident/problem management for the platform. Data & integration Build integrations with upstream sources (trades/positions, reference data, market data, corporate actions) and downstream consumers (collateral, calls/notifications, reporting, finance, risk). Implement strong controls: reconciliations, balances, data lineage, break management, and exception workflows. Ensure consistent exposure/margin explainability across systems and reports. Controls, audit, and regulatory readiness Ensure the platform supports audit/regulatory inquiries with clear documentation, evidence, and timely remediation. Implement change management, access controls, and segregation-of-duties-aligned workflows for sensitive parameters/configurations. Required qualifications Senior engineering leadership experience building and running mission-critical financial risk/margin platforms in production. Demonstrated hands-on expertise with CCP margin methodologies (e.g., SPAN, TIMS ) and ability to implement methodology logic in production-grade systems. Demonstrated experience with prime/broker-dealer margin frameworks including FINRA Portfolio Margin , FINRA 4210 , Regulation T , SEC 15c3-1 (interpretation-to-implementation experience strongly preferred). Strong background in distributed systems and performance engineering; experience designing low-latency calculation services and/or high-throughput batch + streaming hybrids. Proven track record of operational excellence: on-call leadership, incident management, root cause analysis, and reliability improvements. Excellent stakeholder management skills across Front Office, Risk, Operations, Finance, and Control functions. Preferred qualifications Experience integrating with CCPs/clearing venues and supporting cleared derivatives margining workflows end-to-end. Experience implementing model/rule governance: parameter/versioning, reproducibility, approvals, validation support, and audit trails. Experience modernizing legacy risk platforms (monolith-to-services, batch-to-event-driven, data platform upgrades). Strong knowledge of margin drivers across asset classes (e.g., listed derivatives, equities, options, fixed income financing, FX, derivatives) and portfolio/position netting concepts. Technical skills Architecture: Public Cloud (AWS), distributed systems (JDK 21+, Spring Boot), API/service design, event-driven patterns, batch scheduling. Data: strong SQL and NoSQL (Oracle, Cassandra, MongoDB); data lineage/quality controls; streaming/queueing experience (Kafka, IBM MQ). Engineering: CI/CD, automated testing strategies (unit/integeration/regression), performance and resiliency testing. Production: Observability, alerting, capacity planning, and disciplined release/rollback practices.