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.