Lead Software Engineer - Full Stack/AI Engineering Focus

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible. As a Lead Software Engineer at JPMorganChase within the Commercial & Investment Bank - Digital & Platform Services team, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives. Job responsibilities Design, develop, and deliver scalable, secure, and resilient full-stack solutions using Java/Spring Boot, React, and TypeScript, applying strong engineering judgment to meet functional and non-functional requirements while solving complex business and technical challenges. Own the end-to-end delivery lifecycle for strategic platform capabilities and application features, including requirements analysis, solution design, development, testing, deployment, production support, and continuous improvement. Lead the design and development of cloud-native, containerized microservices and platform services, emphasizing domain-driven design, API-first development, performance optimization, security, maintainability, and operational excellence. Drive technical architecture and design decisions across the technology stack, collaborating with product managers, architects, and engineering teams to ensure alignment with enterprise architecture standards and long-term technology strategies. Build and enhance high-performance backend services and APIs (REST/GraphQL), integrating with enterprise platforms, relational databases, search technologies, and distributed data systems. Develop modern operational and administrative user interfaces using React and TypeScript, delivering intuitive experiences that improve platform usability, productivity, and supportability. Design and implement event-driven and streaming architectures leveraging Kafka, including event modeling, schema governance, topic strategy, and resilient producer-consumer patterns to enable scalable and loosely coupled systems. Champion engineering excellence through code reviews, troubleshooting, refactoring, performance tuning, and mentoring, while raising quality standards across the team. Lead initiatives to improve application reliability, observability, and operational stability through automation, proactive monitoring, distributed tracing, incident management, root cause analysis, and continuous reduction of technical debt. Leverage enterprise-approved AI-assisted engineering tools and platforms to accelerate software delivery, improve developer productivity, automate repetitive tasks, and enhance code quality while adhering to established governance, security, and validation practices. Evaluate, design, and implement AI-powered and agentic solutions that optimize software development, operational workflows, system support, and engineering processes, ensuring measurable business and productivity outcomes. Required qualifications, capabilities, and skills Formal training or certification on software engineering concepts and 5+ years applied experience 10+ years of hands-on software engineering experience building and supporting enterprise-scale applications. Strong expertise designing and developing backend services using Java, Spring Boot, distributed systems, and microservice architectures. 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 Hands-on experience building and consuming APIs using REST and/or GraphQL . Strong experience with relational databases, SQL optimization, and data access patterns. Experience implementing event-driven and streaming architectures using Kafka or equivalent messaging platforms. Experience building modern frontend applications using React and TypeScript. Experience with observability and operational tooling such as Splunk, Grafana, Kibana, ELK, OpenTelemetry, Postman, or equivalent platforms. Proficiency with modern engineering tooling including Git, GitHub, Maven, Jenkins, SonarQube, IntelliJ IDEA, VS Code, Jira, and Confluence. Preferred qualifications, capabilities, and skills Working knowledge of Python with experience using Python for automation, data processing, or AI-enabled solutions is highly desirable Experience designing and deploying AI agents and agentic workflows for software engineering, operations, or business process automation. Understanding of Model Context Protocol (MCP) and modern AI integration patterns. Knowledge of prompt engineering techniques, AI workflow design, and human-in-the-loop systems. Experience creating agentic automations that improve SDLC productivity, testing, code reviews, documentation generation, CI/CD operations, or incident management. Demonstrated ability to establish governance, validation, and quality controls for AI-generated code and solutions. Working knowledge of Elasticsearch/OpenSearch, including index design, query optimization, and operational management.