Director of Software Engineering

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 Director of Software Engineering at JPMorganChase within the within the Commercial and Investment Bank, you will own a dual mandate across platform/build (Snowflake enablement, reusable capabilities, reliability, security/controls) and business-facing value delivery (merchant and sales insights, risk and loss reduction, operational efficiency). You will role partner closely with Product, Sales, Operations, Architecture, and Risk/Controls to deliver scalable capabilities and outcomes the field can use immediately. This is a hands-on technology leadership role with a high bar for engineering excellence, including code quality, secure-by-design development, automated testing, CI/CD discipline, and operational readiness.

Drives Snowflake-based analytics/AI enablement with governed data products, secure access, scalable patterns, and performance and cost guardrails. Defines reference architectures and reusable components with engineering and platform teams (e.g., payments-scale aggregation, merchant entity resolution). Drives delivery excellence through agile practices, milestone execution, and rigorous dependency management. Operates a production-grade SDLC for data/AI products: CI/CD, automated testing, observability, runbooks, incident response, and rollback. Owns the Merchant Payments analytics and AI roadmap aligned to measurable outcomes (e.g., TPV growth, authorization uplift, fraud and chargeback loss reduction, onboarding cycle time reduction, merchant experience). Delivers analytics products end-to-end (dashboards and KPIs, self-serve analytics, predictive and decision support) with adoption and lifecycle ownership. Sets and enforces code quality and quality gates (reviews, static analysis, secure coding, unit and integration testing). Drive timely delivery through strong execution mechanics (milestones, dependency management, CI/CD automation, release discipline). Sponsors governance across ownership and stewardship, metadata and lineage, data quality SLAs, retention and access controls, and dataset certification. Standardize critical metric definitions to reduce drift and reconciliation (e.g., TPV, authorization rate, losses, disputes and chargebacks). Run governance forums and issue and remediation processes aligned to delivery priorities. Enables sales and business teams with timely, trusted insights that drive targeting, retention, and portfolio actions. Leads multi-disciplinary teams (analytics, data science, product, engineering, governance) including hiring, coaching, and performance management. Manages budget and capacity planning, partner engagement as needed, and ROI and value tracking tied to outcomes. Sets direction and governance for agentic AI-enabled engineering and SDLC/TLM automation within a technical area to drive measurable improvements in speed, quality, and operational outcomes (e.g., AI-orchestrated delivery workflows, release readiness controls, automated test modernization, and incident triage acceleration), while establishing guardrails for validation, security, resiliency, traceability, and reuse across teams. Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation and support capacity unlock initiatives at scale Required qualifications, capabilities, and skills 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 Track record delivering enterprise analytics and AI solutions end-to-end, from intake and roadmap to production, adoption, and ongoing operations. Demonstrated engineering leadership with strong