Overview In this role, you will shape the future of AI-enabled payment platforms within JPMorganChase's Commercial Card group. You will partner with product and engineering to define architecture, guide technical decisions, and contribute hands-on to design and implementation of high-quality solutions. You'll influence cloud, data, and AI-adjacent systems to deliver scalable, resilient capabilities that drive meaningful business outcomes. This position offers the chance to lead architecture governance, champion modern tools and SDLC practices, and mentor engineering teams in a collaborative, innovative environment.
Compensation / Benefits- comprehensive health care coverage
- retirement savings plan
- tuition reimbursement
- mental health support
- backup childcare
- on-site health and wellness centers
Responsibilities- Represent Commercial Card platforms in architecture and governance forums
- Provide feedback on architecture standards and AI/automation guardrails in regulated environments
- Evaluate existing and emerging technologies, including AI-assisted development tools
- Provide technical guidance to engineering teams, product partners, contractors, and vendors for AI-augmented workflows
- Design, develop, review, and debug secure, high-quality production code and reference implementations
- Influence product design and implementation for scalability, resiliency, and intelligent automation
- Serve as a subject-matter expert within a defined domain
- Advocate approved frameworks, AI-enabled SDLC practices, and continuous improvement
- Influence stakeholders to adopt modern technologies, patterns, and delivery models
- Promote collaboration, inclusion, continuous learning, and responsible AI adoption
Key requirements- Formal training or certification on software engineering concepts
- 5+ years of applied software engineering experience
- Hands-on experience with system design, development, testing, and operational stability
- Advanced proficiency in one or more programming languages, platforms, or architectural styles
- Solid knowledge of software architecture with depth in cloud, distributed systems, data, or AI/ML-adjacent architectures
- Ability to solve complex design problems independently
- Practical experience building and operating cloud-native solutions
- Experience evaluating and recommending current and emerging technologies aligned to architecture goals
- Commitment to teamwork, inclusion, and mentoring engineers
- Comfort working in AI-augmented development environments
- teamwork
- inclusion
- mentoring less-experienced engineers
- cloud-native solutions
- AI/ML adjacent architectures
- AI-enabled SDLC practices
