Senior Lead Software Engineer - Java, React, AI

As a Senior Lead Software Engineer within the AI & ML Data Platforms team at JPMorganChase, you will guide engineering efforts to deliver trusted, scalable technology. You’ll lead technical direction, code with quality and security in mind, and share expertise across the engineering community. You’ll influence design, promote cutting-edge practices, and foster an inclusive team culture. This role combines hands-on development with strategic impact to support mission-critical financial technology initiatives.

• Provide technical guidance to business and technical teams, contractors, and vendors
• Develop secure, high-quality production code and review others’ code
• Drive product design decisions and influence technical operations
• Serve as SME in one or more focus areas and share best practices
• Contribute to engineering community by advocating firmwide frameworks and practices across the SDLC
• Promote adoption of leading-edge technologies within the team
• Foster diversity, inclusion, and respectful collaboration
• Drive adoption of enterprise AI-assisted engineering practices to improve code quality, speed, and outcomes with standardized validation
• Utilize SDLC tools and AI-assisted development and automation to boost automation value

• Formal training or certification in software engineering concepts
• Hands-on experience in system design, application development, testing, and operational stability
• Advanced proficiency in one or more programming languages with emphasis on code quality
• Deep knowledge of software applications and technical disciplines (cloud, AI, ML, mobile)
• Ability to work independently with minimal oversight
• Practical cloud-native experience with scalability, resiliency, and security principles
• Background in Computer Science, Computer Engineering, Mathematics, or related field
• Experience with enterprise-authorized AI-assisted software development tools and evaluating AI outputs for correctness, performance, and security
• Understanding of responsible AI use in engineering workflows and security considerations

• leadership and mentoring
• clear communication
• collaboration across cross-functional teams
• cloud computing (general)
• AI/ML platforms
• enterprise AI-assisted development tools