Director of Software Engineering, Acceleration & Modern Engineering Practices (Asset Management)

If you are looking for a game-changing career, working for one of the world's leading financial institutions, you’ve come to the right place.

As a Director of Software Engineering at JPMorganChase within the Asset & Wealth Management, Asset Management Acceleration Pod Team, you, you provide expertise and engineering excellence as an integral part of an agile team to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. Leverage your advanced technical capabilities and collaborate with colleagues across the organization to drive best-in-class outcomes across various technologies to support one or more of the firm’s portfolios.

This Executive Director Software Engineering leader will stand up and run the Asset Management Acceleration Program (“Acceleration Pod”) a dedicated, cross-functional delivery pod that executes a structured flow from idea → validation → pilot/POC → demo → production, with tight governance and rapid iteration to deliver measurable business outcomes. You will combine deep hands-on engineering expertise with senior leadership to drive modern software delivery (CI/CD, testing modernization, cloud-native architecture, APIs/integration, data modeling) and establish an operating model that emphasizes small, focused scopes; reuse of standardized components; short sprint cycles and fast experimentation.

Job responsibilities

• Creates complex and scalable coding frameworks using appropriate software design frameworks

• Develops secure and high-quality production code, and reviews and debugs code written by others

• Architects and governs agentic AI-enabled engineering workflows (using enterprise-authorized tools within the work environment) to improve delivery speed, code quality, and operational outcomes at scale (e.g., AI-driven PR review assistance, test generation/maintenance, release readiness checks, incident triage and root-cause acceleration), while defining guardrails for validation, security, resiliency, 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 at scale.

• Set technical direction for architecture, integration patterns, API strategy, data modeling, and platform engineering while modernizing engineering practices (CI/CD pipelines, automated testing frameworks, release readiness controls, observability, and production support operating procedures) to accelerate delivery and maintain reliability, security, and maintainability

• Run pod governance (council + standups) to prioritize work, clear blockers, and drive Go/No-Go decisions, partnering with senior sponsors to align outcomes, resourcing, and decision rights.

• Lead the end-to-end Acceleration Program lifecycle from intake through production rollout (including structured validation, pilot/POC execution, demos, and production hardening/approval processes) while establishing and running sprint-based delivery to drive transparency, stakeholder engagement, and continuous improvement

• Build delivery guardrails that reduce common failure modes observed in innovation efforts (e.g., organizational silos, technical debt accumulation, weak user engagement, and process/adoption barriers).

• Institutionalize reuse of proven components (“reuse 80% of the stack”) and establish guardrails and reference implementations that reduce time-to-deliver and improve consistency across initiatives

• Influences leaders and senior stakeholders across business, product, and technology teams

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

• CI/CD (build/release automation, quality gates, deployment strategies)

• Testing frameworks & automation (unit/integration/contract tests; test strategy and modernization)

• Python OR Java (production services, data applications, automation tooling)

• UI development experience (e.g., modern web UI frameworks, component-based design systems, front-end testing and performance optimization), especially for workflow-heavy internal platforms.

• Data modeling (conceptual/logical/physical; analytics and operational data considerations)

• Architecture (distributed systems, resiliency, performance, maintainability)

• Integration & APIs (REST/event-driven patterns, governance, versioning, security)

• AWS services (practical, production experience; networking, compute, storage, security/IAM, monitoring)

• Proven ability to drive cross-functional alignment (product, business, risk/control, architecture, platform teams) and operate effectively in a governance model with senior stakeholders

Preferred qualifications, capabilities, and skills

• Experience running a “working backwards” or outcome-first delivery model, including crisp problem framing, acceptance criteria, and success metrics

• Demonstrated success scaling delivery velocity without sacrificing quality (e.g., redesigning CI/CD and testing philosophy to match higher throughput)

• Experience building durable adoption mechanisms (early adopter/champion strategies, measurable adoption metrics, and feedback loops)

• Familiarity with enterprise-approved AI-assisted development tools and patterns (e.g., code assistants, agentic workflows, test generation/triage automation) and how to operationalize them with appropriate guardrails in day-to-day engineering.

• Experience partnering with UX/design to translate user journeys into intuitive experiences, applying UX best practices (research, prototyping, usability testing), and incorporating UX designers into agile delivery to close user-engagement gaps.

• Prior experience in Asset Management technology domains (portfolio, client, research, trading, operations, data/analytics platforms)