Senior Director of Software Engineering - AI Development | Engineering Services & Platforms

JPMorgan Chase & Co.•Columbus, OH

About The Position

As a Senior Director of Software Engineering at JPMorganChase for Engineering Services & Platforms within the Chief Technology Office (CTO), 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. As the Senior Director of Software Engineering you will work on a rare greenfield opportunity to solve for one of the fastest-growing threats in enterprise technology - Software Dependency Risk. As AI-assisted development accelerates the adoption of open-source and commercial packages across the firm, understanding what software your applications depend on — and whether it's healthy, secure, and compliant — has never been more critical. JPMorgan Chase's answer to that challenge: a firm-wide platform that gives 60,000 developers and their engineering leaders visibility into the dependency health of 6,000+ applications. We are past ideation and into the market — an early product in hand, the roadmap ahead, and a mandate to build something that becomes foundational infrastructure for how the firm manages software risk at scale.

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.
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.
Proven track record of shipping Version 1 products: taking something from concept through first release into iterative improvement.
Genuine enthusiasm for and practical experience with AI-first development practices — using LLMs and agentic tools to accelerate software delivery.
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 with hiring, developing, and recognizing talent.
Extensive practical cloud native experience - AWS.

Nice To Haves

Experience in customer-facing, data-intensive products — you understand what it means to build for people who depend on your platform to do their jobs.
Financial services or other regulated industry experience is a plus, not a requirement — intellectual honesty, rigor, and comfort with compliance constraints matter more than a specific industry background.
Low ego, high ownership: you can influence without authority, build relationships across a complex organization, and stay close to the work.

Responsibilities

Build and lead the engineering team.
Own the engineering organization for Dependency Explorer end-to-end — hiring, structure, culture, and performance.
Lead and grow a team of engineers and engineering managers; this role is designed to scale into a managers-of-managers structure as the platform grows.
Partner closely with product managers and designers distributed across the US and UK to ship a cohesive, high-quality product.
Lead delivery of the core platform build-out: data ingestion pipelines, dependency graph modeling, developer-facing surfaces, and firm-wide integration.
Make and own key architectural decisions on a modern AWS and Java stack.
Navigate the complexity of building at firm-wide scale — thousands of applications, dozens of lines of business, diverse ecosystems.
Sets strategy and operating standards for agentic AI-enabled engineering across a portfolio (using enterprise-authorized tools within the work environment) to drive measurable improvements in delivery speed, reliability, and code quality (e.g., AI-orchestrated SDLC/TLM automation, release readiness gating, incident triage/root-cause acceleration, and large-scale refactoring/test modernization), while defining guardrails for validation, security, resiliency, and reuse across teams and functions.
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.
Build an agentic-first development practice — where AI tools (including Claude) are embedded into how the team designs, codes, reviews, and ships.
Hire engineers who are excited by this model and coach those who are learning it.
Set the standard for what a high-performing, AI-augmented engineering team looks like inside a regulated, large-scale enterprise.
Operate as a senior engineering voice, building relationships and credibility across teams beyond your direct organization.
Represent engineering in cross-functional discussions with security, risk, compliance, and firm-wide platform partners.
Engage with senior stakeholders with clarity and conviction — translating deep technical work into business impact.