Lead Software Engineer

Job Description: Join a team where your engineering work accelerates how machine learning is built, governed, and delivered across JPMorganChase. You will create platform capabilities that help teams move from ideas to production with confidence. If you enjoy building scalable systems and improving developer experience, this role offers meaningful impact and growth. As a Software Engineer III at JPMorganChase within the Corporate Artificial Intelligence and Machine Learning Data Platforms team, you will build and enhance products that support the end-to-end machine learning lifecycle, including model operations, data development (including processing and data annotation), and governance tooling. You will collaborate with engineers, system architects, product managers, data scientists, and research partners to deliver reliable, secure, and user-friendly platform services. Job responsibilities Build and enhance platform services for model registries, feature registries, promotion policies, and governance workflows Design and deliver capabilities for data preparation, annotation workflows, lineage, and audit trails Develop cloud-native services and application programming interfaces that scale across development and production environments Implement large language model-powered features (prompt design, agent workflows, tool integration, retrieval) with strong controls and evaluation practices Produce and maintain architecture and design artifacts; ensure solutions meet performance, resiliency, and security expectations Use approved AI-assisted development tools responsibly, validating outputs through code review, testing, and secure coding practices Partner with product and engineering stakeholders to prioritize roadmap items and improve platform usability Analyze operational metrics and user feedback to improve reliability, usability, and platform adoption Identify and remediate issues in systems and data; improve code quality, observability, and maintainability Required qualifications, capabilities and skills Formal training or certification on software engineering concepts and 3+ years applied experience Experience building and delivering backend or platform services using modern architecture patterns, including microservices, reactive architectures, or event-driven architectures Experience developing and deploying large language model-powered solutions using prompt design, agent workflows, tool integration, and retrieval techniques Proficiency in at least two modern languages or frameworks such as Python, Java, JavaScript, React, or Node.js Experience building and consuming RESTful application programming interfaces, including performance tuning in large-scale applications Experience with cloud platforms and containerization or orchestration tools such as Docker and Kubernetes Experience with relational and non-relational databases such as PostgreSQL, MongoDB, Redis, Elasticsearch, or Cassandra Experience with engineering practices including refactoring, design patterns, automated testing, continuous integration, continuous delivery, and application security Hands-on experience using approved AI-assisted software development tools, with the ability to validate and refine outputs for correctness, performance, and security Preferred qualifications, capabilities and skills Proficiency in Go or Terraform for automation, tooling development, or platform service implementation Working knowledge of machine learning frameworks such as PyTorch, TensorFlow, Hugging Face, or scikit-learn for model integration and operationalization Exposure to multi-cloud or hybrid cloud architectures and platform portability strategies Experience building governance controls for model lifecycle management, including approvals, policy enforcement, and auditability