DescriptionYour 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 JPMorgan Chase within the Consumer and Community Banking Risk AI/ML Model Engineering team, you lead multiple technical areas, manage the activities of multiple departments, and collaborate across technical 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. You will be responsible to leading the integration of various model platforms and models that support Chase’s card, consumer and business banking, auto and mortgage portfolio plus regulatory functions.
Job responsibilities
Leads multiple technology and process implementations across departments to achieve firmwide technology objectives
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.
- Provide hands-on thought leadership in building cloud-based Model integration solution architectures.
- Demonstrate a solid understanding of consumer financial products, data systems/environments, and processes required to implement Risk and Finance models.
- Directly manages multiple areas with strategic transactional focus
- 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
- Champions the firm’s culture of diversity, opportunity, inclusion, and respect
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 10+ years applied experience. In addition, 5+ year of experience leading technologists to manage, anticipate and solve complex technical items within your domain of expertise and more broadly across the organization
- 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 complex projects supporting system design, testing, and operational stability
- Experience building application frameworks and/or developing platforms.
- Background with machine learning frameworks and big data technologies such as Databricks, Snowflake, and Spark.
- 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 with hiring, developing, and recognizing talent
- Extensive practical cloud native experience
- Expertise in Computer Science, Computer Engineering, Mathematics, or a related technical field
Preferred qualifications, capabilities, and skills
- Experience working at code level