Senior Lead Architect – Commercial Card Payments Technology

JPMorganChase•Chicago, IL

19d

About The Position

As a Senior Lead Architect in JPMorganChase’s Payments Technology – Commercial Card organization, you will help shape architecture for modern, scalable, resilient, and AI-enabled payment platforms. You will partner with product and engineering teams to define architecture, guide technical decisions, and contribute hands-on to the design and implementation of critical Commercial Card capabilities. The role drives business outcomes and helps shape target-state architecture across cloud, data, and AI-adjacent systems. You will represent platform or product areas in architecture and technical governance forums, guide technology evaluations, and advise teams on architecture standards and technical approaches. You will also design, develop, review, and debug secure production code; provide engineering guidance; and promote collaboration, inclusion, continuous learning, technical excellence, and responsible AI adoption.

Requirements

Formal training or certification in software engineering concepts and at least 5 years of applied experience.
Strong hands-on experience delivering system design, application development, testing, and operational stability.
Advanced proficiency in one or more programming languages, platforms, or architectural styles.
Solid knowledge of software architecture, application design, and technical processes, with depth in one or more domains such as cloud, distributed systems, data, or AI/ML-adjacent architectures.
Ability to independently solve complex design and functionality problems with limited oversight.
Practical experience building and operating cloud-native solutions.
Ability to evaluate current and emerging technologies, including AI-assisted development and automation tools, and recommend solutions aligned with architecture goals.
Demonstrated commitment to teamwork, inclusion, and mentoring less-experienced engineers.
Comfort working in AI-augmented development environments to accelerate design, coding, testing, and analysis.

Nice To Haves

Experience designing or modernizing commercial card or payments systems, including issuing, authorization, clearing, settlement, or posting flows.
Working knowledge of card processing ecosystems, including processors, card networks, tokenization, and integration patterns.
Experience contributing to fraud prevention or risk solutions, including rules-based or data-driven approaches.
Familiarity with ledger concepts, posting models, reconciliation, and data consistency in distributed systems.
Exposure to platform modernization initiatives, such as legacy transformation, cloud migration, or API enablement.
Experience with API-led and event-driven architectures, including microservices and asynchronous messaging.
Understanding of resiliency and scalability patterns, including multi-AZ or multi-region designs.

Responsibilities

Represent Commercial Card platforms or product areas in architecture and technical governance forums.
Provide feedback on architecture standards and propose improvements, including guardrails for AI use and automation in regulated environments.
Guide evaluation of existing and emerging technologies, including AI-assisted development tools and intelligent platform capabilities.
Provide technical guidance to engineering teams, product partners, contractors, and vendors, enabling AI-augmented engineering workflows.
Design, develop, review, and debug secure, high-quality production code, including reference implementations and architectural patterns.
Influence product design, application behavior, and technical implementation decisions, with a focus on scalability, resiliency, and intelligent automation.
Serve as a recognized subject-matter expert within a defined domain or capability area.
Advocate firm-approved frameworks, tools, AI-enabled SDLC practices, and continuous improvement within the engineering community.
Influence peers and stakeholders to consider modern, fit-for-purpose technologies, patterns, and delivery models.
Promote collaboration, inclusion, continuous learning, technical excellence, and responsible adoption of AI.