Senior Director of Software Engineering

JPMorgan Chase & Co.•Columbus, OH

About The Position

As a Senior Director of Software Engineering at JPMorgan Chase within the Marketing Technology group, you will lead multiple technical areas, manage the activities of multiple departments, and collaborate across technical domains. Your expertise will be 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. This role offers an opportunity to make a real impact and shape the future of financial services.

Requirements

10 + years of experience managing Software Delivery teams and enterprise products.
Experience developing or leading large or cross-functional teams of 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.
Experience leading complex projects supporting system design, testing, and operational stability.
Experience with hiring, developing, and recognizing talent.
Extensive practical cloud native experience.

Nice To Haves

Advanced proficiency in managing full stack technical delivery teams and enterprise products.
Hands-on expertise as a Web or Full Stack Developer, IT Consultant, or related technical role.
Deep knowledge of big data processing frameworks (e.g., Spark, Flink, Storm) and stream processing with Kafka.
Strong understanding of data design, modeling principles, and architecture patterns (data lake, lakehouse, data mart, data fabric, data mesh).
Advanced experience with cloud services and cloud-native data technologies (AWS EMR, Glue, Lambda, MSK, RDS, DocumentDB; AWS preferred).
Expertise in semantic technologies, modeling, graph databases (Neo4J, Datastax Graph, AWS Neptune), and graph processing languages (Gremlin, Cypher, SparQL).
Advanced hands-on knowledge of web or middleware security solutions and server-side web technologies.

Responsibilities

Leads multiple technology and process implementations across departments to achieve firmwide technology objectives.
Directly manages multiple areas with strategic transactional focus.
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.
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.