SR Director of Software Engineering – Lending Technology

JPMorgan Chase & Co.•New York, NY

1d•$232,750 - $325,000

About The Position

You will lead the modernization of our commercial lending processes and the technology that powers them. You will work directly with bankers and product partners to deliver simpler workflows, stronger controls, and faster client outcomes. You will set engineering standards that prioritize reliability, security, and speed—without sacrificing resiliency or cost discipline. You will be a hands-on technical leader who develops talent and stays current through continuous learning. As a Senior Director of Software Engineering at JPMorganChase within the Commercial and Investment Bank Lending Technology team, you lead leaders and senior engineers to design and modernize commercial lending workflows and platforms. You partner closely with bankers, product, and operations to turn business needs into roadmaps and measurable delivery. You set a high bar for reliability, secure development, and operational excellence while increasing delivery velocity. You use data to guide decisions and ensure implementations are correct. You proactively manage organizational health, staffing, vendor strategy, and budget.

Requirements

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
Demonstrated experience leading leaders (managers of managers) and senior technical staff in complex engineering organizations
Proven ability to modernize workflow-heavy enterprise systems, including process redesign and platform modernization
Strong engineering fundamentals across system design, distributed systems, reliability engineering, secure development, and software delivery practices
Demonstrated ability to partner with non-technical stakeholders (including bankers and operations) and drive alignment on scope, risk, cost, and timelines
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
Budget ownership experience, including planning, forecasting, and proactive expense management (headcount, vendor, and platform costs)
Quantitative foundation to apply financial math to lending workflows; coursework or degree in calculus or statistics (or equivalent applied experience)
Strong communication skills with the ability to be concise, direct, and credible with both engineers and business partners

Nice To Haves

Experience in lending, credit, underwriting, loan origination/servicing, or adjacent financial services workflows
Experience building data-intensive platforms and using metrics to manage reliability, delivery, and product outcomes
Experience with cloud platforms, platform engineering, and automation at scale
Familiarity with risk, controls, auditability, and regulatory expectations in financial services

Responsibilities

Set and uphold engineering standards across architecture, reliability, security, and delivery for commercial lending modernization
Partner with bankers, product, and operations to translate business needs into clear roadmaps, well-defined scope, and measurable outcomes
Drive operational excellence through automation, observability, resiliency patterns, and disciplined incident management to improve availability and speed-to-delivery
Lead design reviews and critical-path technical decisions; mentor senior engineers and engineering leaders
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
Make disciplined build, buy, and reuse decisions based on business value, risk, and total cost of ownership
Establish a data-driven culture by defining metrics, analyzing outcomes, and using insights to improve product decisions and controls
Own budget planning, forecasting, and expense management; proactively adjust spend, staffing, and vendor usage to avoid surprises
Build and retain high-performing teams through structured hiring, performance management, and career development practices