Lead Software Engineer, Platform & Experience Journeys

JPMorgan Chase & Co.•New York, NY

23h•$152,000 - $215,000

About The Position

As a Lead Software Engineer at JPMorgan Chase within the Consumer & Community Banking’s Customer Platform team, you are an integral part of an agile team that works to enhance, build, and deliver trusted, market-leading identity and onboarding solutions in a secure, stable, and scalable way. You will play a key role in designing and delivering a shared identity platform that supports customer onboarding, identity verification, and trust services across multiple products and lines of business.

Requirements

Formal training or certification on software engineering concepts and 5+ years of applied experience.
Experience designing and engineering workflow orchestration for policy-driven customer journeys and reusable sub-journey components.
Experience designing or operating event-driven architectures using Kafka or equivalent messaging platforms.
Hands-on full-stack engineering experience building production services and user-facing tools, including backend APIs, front-end interfaces, testing, and operational support
Experience building or maintaining CI/CD pipelines and deployment automation for secure, repeatable releases across environments
Working knowledge of role-based access control, service ownership boundaries, and API contract design in distributed systems
Experience using AI-assisted development tools and applying AI capabilities to build, test, improve, or operate software solutions, with responsible attention to quality, security, and data sensitivity.
Experience with distributed tracing and observability across multi-service journey execution
Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices
Experience with distributed tracing and observability across multi-service journey execution

Nice To Haves

Prior experience leading migration from bespoke service implementations to reusable component models in a regulated industry.
Experience designing multi-tenant, multi-LOB platforms with role-based access control enforced at organizational boundaries.
Experience building or enabling AI-assisted or AI-enabled software solutions, including selecting appropriate tools, establishing responsible usage patterns, and aligning implementation with quality, security, and compliance expectations.
Experience in a co-development or strategic vendor partnership with active roadmap influence
API platform and developer portal engineering at enterprise scale

Responsibilities

Design and build reusable identity sub-journey components to support onboarding processes for multiple lines of business
Build the automation layer that moves configured identity journeys from approval to production deployment, including policy validation, release controls, and complete audit-trail generation.
Establish the eventing framework and observability standards that make multi-service journey execution visible, debuggable, and compliant
Build developer-facing tools, including API contracts, sandbox environments, and integration templates, that enable line-of-business teams to assemble and deploy compliant identity journeys without an engineering dependency.
Mentor and grow the engineers building alongside you by setting engineering standards, leading rigorous code reviews, and upskilling the team as needed.
Build migration tooling and playbooks that move product teams off legacy bespoke implementations to platform services
Drive responsible adoption of AI-assisted engineering practices, including code review, test acceleration, and incident analysis, with clear team standards for validating AI outputs for correctness, performance, and security.
Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
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.