Sr. Director of Software Engineering

Job Summary

Required Qualifications

• Demonstrate significant experience leading software engineering teams delivering enterprise-grade platforms, including people management, technical leadership, and cross-functional delivery in complex environments.
• Exhibit strong judgment in architecture and design trade-offs, with a track record of building reliable, data-intensive services and integrating with upstream/downstream systems.
• Possess deep knowledge of modern SDLC practices, including CI/CD, automated testing strategies, secure development, and production operations.
• Communicate clearly with both technical and non-technical stakeholders and translate accounting and controls requirements into actionable technical plans and measurable outcomes.
• Bring experience working in environments with a mix of modern and legacy technologies common in financial engineering, including Backend: Java, Spring Boot, Python. Data & Integration: event streaming, APIs, ETL/ELT patterns, data quality framework. Datastores: PostgreSQL/Oracle, distributed query engines, Drools, caching.
• Set clear engineering direction and build a high-accountability environment with measurable delivery outcomes, strong quality gates, and transparent execution.
• Raise engineering standards by driving simplification and continuously improving reliability and operational efficiency.
• Coach and develop engineers and managers through regular feedback, career development plans, and performance management, while actively building diverse pipelines and practicing inclusive leadership.
• Establish effective partnerships with Product, Accounting, and technology stakeholders to ensure requirements are understood, prioritized, and executed with appropriate governance.
• Ensure solutions meet firm security, privacy, and risk policies, including secure coding practices, access controls, segregation of duties considerations, and auditable change management.
• Experience leading multi-organization adoption of agentic AI-enabled engineering operating models (using enterprise-authorized tools within the work environment), including defining governance (human-in-the-loop decisioning, quality gates), measurement frameworks, and secure handling of sensitive inputs/outputs across teams.
• Deep understanding of responsible AI risk, controls, and resiliency/security expectations at scale, with demonstrated ability to advise senior leaders on safe adoption, portfolio governance, and reuse-first strategies.
• Preferred qualifications, capabilities, and skills: Bring experience building technology solutions in Accounting, Finance, Controllers, or Regulatory Reporting environments, including exposure to close processes, reconciliations, subledger patterns, accounting event processing, and financial controls.
• Demonstrate familiarity with data governance concepts, including data lineage, metadata management, and control evidence generation.
• Show experience operating systems in highly regulated environments, including audit engagement support, issue remediation, and operating model maturity.
• Provide prior experience modernizing legacy platforms, decomposing monoliths, and driving cloud adoption within enterprise guardrails.