Lead Software Engineer - Full Stack Java/React

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 Asset & Wealth Management Marketing Technology 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

• Architect, build, and maintain backend services and APIs using Java (preferably Java 17+) and Spring Boot.
• Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems.
• Design RESTful and/or GraphQL interfaces; ensure robust authentication, authorization, and input validation.
• Own system performance, reliability, observability (metrics, logging, tracing), and security best practices.
• Write comprehensive automated tests (unit, integration, end-to-end) and drive CI/CD excellence.
• Lead code reviews, mentor engineers, and promote engineering standards and clean architecture.
• Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems.
• Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture.
• 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.

Required qualifications, capabilities, and skills

• 10+ Years of experience.
• Hands-on practical experience delivering system design, application development, testing, and operational stability.
• Advanced in one or more programming language(s).
• Proficiency in automation and continuous delivery methods.
• Experience with relational databases (PostgreSQL, MySQL) and at least one NoSQL store (e.g., MongoDB).
• Knowledge of messaging/streaming (Kafka, RabbitMQ) and asynchronous processing.
• Solid testing practices: JUnit, Mockito, Spring Test; front-end testing with Jest, React Testing Library, Cypress/Playwright.
• Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security.
• Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.).
• 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.

• Develop high-quality, reusable React components (React 18+, TypeScript) and front-end features
• Hands-on with AWS services: ECS/EKS or Lambda, API Gateway, S3, CloudFront, RDS/Aurora, DynamoDB, SNS/SQS, CloudWatch.
• Infrastructure-as-Code (Terraform or CloudFormation).
• Experience with Kubernetes and service mesh (Istio/Linkerd) a plus.
• Observability tooling: OpenTelemetry, Grafana, Prometheus.