Senior Director of Software Engineering - Data and AI
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Description -----------
Your opportunity to make a real impact and shape the future of financial services is waiting for you. Let’s push the boundaries of what's possible together.
As a Senior Director of Software Engineering at JPMorganChase within the Commercial and Investment Bank Operations team, you lead multiple technical areas, manage the activities of multiple departments, and collaborate across Data and AI domains. Your expertise is applied cross-functionally to drive the adoption and implementation of technical methods within various teams and aid the firm in remaining at the forefront of industry trends, best practices, and technological advances.
Job Responsibilities
- Sets the direction for Data and AI technology platforms.
- Directly manages multiple areas with strategic focus on Transactional and Analytics Data and AI systems
- 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.
- Enable existing or new data applications and related data models to be ready for consumption by AI Agents
- Provides leadership and high-level direction to teams while frequently overseeing employee populations across multiple platforms, divisions, and lines of business
- Acts as the primary interface with senior leaders, stakeholders, and executives, driving consensus across competing objectives
- Manages multiple stakeholders, complex projects, and large cross-product collaborations
- Influences peer leaders and senior stakeholders across the business, product, and technology teams
Required qualifications, capabilities, and skills
- Bachelor’s or Master’s degree in Computer Science, Engineering, or related field
- 15+ years of experience in software engineering, with at least 5 years building and managing large scale, critical and complex distributed data management systems.
- Formal training or certification on software engineering concepts and 10+ years applied experience. In addition, 5+ years of experience leading technologists to manage, anticipate and solve complex technical items within your domain of expertise
- Experience developing or leading large or cross-functional teams of Data and AI technologists
- Demonstrated prior experience influencing across highly matrixed, complex organizations and delivering value at scale
- 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.
- Proven track record of delivering complex trading or financial systems in a global banking environment
- Experience leading projects supporting complex data system design, data quality testing, and operational stability
- Ability to influence and drive change across technology and business teams
- Experience with hiring, developing, and recognizing talent
Preferred qualifications, capabilities, and skills
- Strong data engineering foundations including experience developing and managing complex data models, extensible ETL/ELT patterns and multi-modal Search techniques
- Proficiency with the modern data stack: SQL plus at least one general-purpose language (commonly Python/Java/Scala)
- Distributed systems & cloud literacy: understanding of performance, partitioning, storage formats, compute engines, and cloud services.
- Data quality & observability mindset: automated tests, monitoring/alerting, SLAs/SLOs, lineage, and incident response basics.
- Proven track record of delivering complex trading or financial systems in a global banking environment
- Experience with hiring, developing, and recognizing talent
This position is subject to Section 19 of the Federal Deposit Insurance Act. As such, an employment offer for this position is contingent on JPMorgan Chase’s review of criminal conviction history, including pretrial diversions or program entries.
About JP Morgan Chase
JP Morgan Chase is a global financial services provider that offers investment banking, asset management, treasury, and other services.
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