Job Summary:
As the Lead Software Engineer at JPMorgan Chase within the Wholesale Credit Risk team, you will play a pivotal role in designing and implementing scalable hybrid cloud solutions. You will collaborate with development leads and senior stakeholders to deliver robust solutions, while mentoring team members and fostering a collaborative environment. This opportunity allows you to leverage your technical expertise in hybrid cloud architecture and coding to promote technical excellence and innovation.

Job Responsibilities:

• Architect, design, and implement scalable hybrid cloud solutions for transactional, analytics and RAD workloads.
• Write and review high-quality code, ensuring adherence to best practices and standards.

• 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.

• Collaborate with development leads and cross-functional teams to deliver robust solutions.

• Conduct code reviews and provide constructive feedback to drive technical excellence.
• Present technical concepts and project updates to senior stakeholders.
• Prioritize tasks effectively, balancing urgent needs with strategic progress.
• Mentor and support team members, fostering a collaborative and helpful environment.

Required qualifications, capabilities and skills:

• Formal training or certification on hybrid cloud architecture concepts and 5+ years applied experience.
• Proven experience in hybrid cloud architecture (AWS, Azure, GCP, or private cloud).

• Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.

• 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

• Deep understanding of distributed systems, data pipelines, and analytics platforms.
• Experience with CI/CD, DevOps, and modern software engineering practices.
• Excellent interpersonal and presentation skills.
• Demonstrated ability to work with development leads and senior stakeholders.

Preferred qualifications, capabilities and skills:

• Action-oriented, decisive, drives results systematically.
• Strong coding skills in languages such as Java, Python, React or similar.
• Skilled at assessing risk and making decisions with a holistic, big-picture perspective.
• Demonstrates a can-do attitude and leads by example.
• Detail-oriented, able to distinguish between important and urgent tasks.
• Prioritizes helpfulness, mentorship, and team development.
• Acts with integrity.