Senior Lead Software Engineer - AI/ML Developer

JPMorganChase is a financial services firm serving consumers, businesses, and communities through a broad range of financial products. The company is seeking a Senior Lead Software Engineer to build, scale, and maintain secure machine learning platforms and infrastructure. The role focuses on ML workflow tools, platform services, automation, reliability, and collaboration with data scientists, ML engineers, and product teams.

Responsibilities:

• Designs, builds, and maintains scalable machine learning platforms and infrastructure to support end-to-end ML workflows
• Develops and optimizes tools for model training, deployment, monitoring, and lifecycle management
• Integrates data engineering, feature management, and model serving capabilities into unified ML platform solutions
• Implements secure, high-quality production code for platform services, APIs, and automation pipelines
• Leads evaluation sessions with data scientists, ML engineers, and product teams to understand requirements and deliver platform features that accelerate ML development and operations
• Ensures platform reliability, scalability, and performance through proactive monitoring, troubleshooting, and continuous improvement
• Produces architecture and design artifacts for platform components, ensuring alignment with enterprise standards and best practices
• Automates infrastructure provisioning, configuration, and CI/CD pipelines for ML platform services
• Contributes to the ML platform engineering community of practice and participate in events that explore new and emerging technologies
• 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