If you are a software engineering leader ready to take the reins and drive impact, we've got an opportunity just for you.
As a Senior Director of Software Engineering at JPMorganChase within the Commercial and Investment Bank post trade accounting group, you lead multiple technical areas, and collaborate across technical domains. Your expertise is applied cross-functionally to drive the adoption and implementation of technical methods within various global teams and aid the firm in remaining at the forefront of industry trends, best practices, and technological advances.
Job Responsibilities
- Owns engineering outcomes for a portfolio of accounting-facing products and services by translating finance requirements into scalable architectures and well-managed backlogs.
- Leads multiple agile pods to ensure consistent delivery, strong quality engineering practices, and predictable throughput aligned to quarterly close cycles and critical reporting timelines.
- Drives end-to-end technology execution across architecture/design reviews, build and test automation, performance and reliability engineering, and operational readiness.
- Partners with Accounting stakeholders to improve process automation, data lineage, reconciliations, and control evidence while reducing operational risk and manual effort.
- Ensures production stability through effective incident management, timely root-cause remediation, and continuous improvement.
- Contributes to hiring, talent development, and succession planning to sustain a culture of ownership, engineering excellence, and risk-aware delivery.
- Sets and scales multi-department strategy for agentic AI-enabled engineering and SDLC/TLM automation (using enterprise-authorized tools within the work environment) to drive firmwide objectives (speed, scalability, reliability, and cost-to-serve), including portfolio-level standards for AI-orchestrated delivery workflows, release governance, automated test modernization, resilience engineering, and incident response acceleration establishes guardrails for validation, security, resiliency, traceability, and reuse.
- Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to drive cross-domain reuse and measurable capacity unlock outcomes across departments.
Required qualifications, capabilities, and skills
- 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.
