Lead Software Engineer - Java/Spring boot/React/AWS

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 JPMorgan Chase within the Consumer and Community Banking Operations Dispute technology, 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: Lead the design, development, and deployment of highly scalable, fault-tolerant, mission-critical distributed systems and cloud modernization initiatives that process high-volume financial transactions with zero-downtime Drive technical design decisions and long-term architecture strategy, making critical choices on technology stack, architectural patterns, and infrastructure solutions while evaluating and introducing emerging technologies that improve team productivity and system capabilities Serve as technical lead for full-stack development, providing hands-on guidance to engineers on complex technical challenges, driving code review excellence, and championing engineering best practices across the team Ensure code quality and security through comprehensive automated testing strategies (unit, integration, end-to-end), static code analysis, and vulnerability scanning 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 cross-functional teams including architects, product owners, and engineering teams to translate business requirements into scalable technical solutions and delivery roadmaps Partner with engineering teams across the organization to define technical scope, API contracts, integration patterns, cross-team dependencies, and end-to-end delivery plans Drive delivery excellence across multiple concurrent initiatives in a fast-paced environment, effectively balancing technical debt, feature development, and operational stability Establish and maintain comprehensive observability frameworks including logging, monitoring, alerting, and distributed tracing to ensure system reliability, rapid incident resolution, and operational excellence Provide L3 production support and serve as technical escalation point for critical issues, collaborating with operations teams to ensure rapid incident resolution, root cause analysis, and system stability Required qualifications, capabilities, and skills: Formal training or certification on software engineering concepts and 5+ years applied experience building enterprise-grade applications Expert-level proficiency in Java, Spring Boot, RESTful API design, and microservices architecture with demonstrated experience designing and building highly scalable distributed systems for high-availability production environments Strong experience with AWS cloud services including EC2, ECS/EKS, Lambda, S3, RDS, SQS/SNS, API Gateway, and CloudWatch with infrastructure-as-code implementation using Terraform Proficiency in front-end development with React JS, including state management (Redux/Context API), component design patterns, and modern JavaScript Proven experience implementing event-driven architectures using message queues (SQS/SNS), streaming platforms (Kafka, AWS MSK), and asynchronous processing patterns for high-throughput systems Strong understanding of application security principles including OAuth2/JWT authentication, encryption at rest and in transit, secrets management, and secure API design 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 Expertise in CI/CD pipelines, continuous delivery methods, end-to-end automation, and automated deployment strategies using modern DevOps tools and practices Proficiency in test-driven development (TDD), comprehensive testing strategies (unit, integration, end-to-end), and code quality practices Expertise in application resiliency patterns (circuit breaker, retry, timeout, bulkhead), observability, and production monitoring using tools like Splunk, Dynatrace, and CloudWatch Preferred qualifications, capabilities, and skills: Knowledge of the financial services industry, regulatory requirements, and their IT systems Experience with Agentic AI solutions, machine learning model integration, or AI-powered automation frameworks Exposure to Camunda BPMN or other workflow orchestration engines for complex business process automation Experience with GraphQL API design and implementation