Lead Software Engineer - Fullstack

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As a Lead Software Engineer at JPMorgan Chase within the Consumer and community banking technology - Business Banking 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
Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problems
Develops secure and high-quality production code, and reviews and debugs code written by others
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.
Lead technical design and delivery of complex full-stack capabilities (Java/Spring Boot + React/Angular).
Drive event-driven patterns using Kafka (idempotency, retries, ordering, error handling).
Establish strong engineering practices (test strategy, automation, CI/CD quality gates, observability).
Own production excellence: incident reduction, RCA prevention, performance tuning, and operational readiness.
Mentor engineers and influence technical direction across squads and partner teams.
Required qualifications, capabilities, and skills
Formal training or certification on software engineering concepts and 5+ years applied experience
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
Deep expertise in Java 8+ / Spring Boot, microservices, and React/Angular.
Strong Kafka/event-driven architecture experience (retries, idempotency, DLQ patterns, schema/versioning).
Experience with SQL databases with data modelling, query optimization, and performance tuning.
Strong NoSQL experience: Cassandra / DynamoDB / Elastic Search (data modeling, reliability, scale).
Strong experience with Cloud Foundry/AWS and CI/CD strategy and execution.
Demonstrated leadership in design reviews, mentoring, and cross-team technical alignment.
Ability to work with tools such as Dynatrace, Splunk, Grafana for observability and monitoring
Experience building applications with resilient, highly available architectures, including consideration for failure modes, recovery, and operational readiness.
Preferred qualifications, capabilities, and skills
Working knowledge of secure engineering practices and designing to meet Cyber Security and Technology Control requirements (e.g., authentication/authorization, secure APIs, data protection, dependency hygiene).
Cross-team delivery leadership, PCI experience and AWS cert are pluses.