Lead Software Engineer- Java, Kafka, AWS, Spark, AI
JPMorgan Chase · Posted Nov 5
Global banking, investment, credit card, mortgage, and asset management services
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About the role
The Consumer and Community Banking - Trust and Security organization builds and delivers trusted technology products in a secure, stable, and scalable way, with this role sitting on an agile team supporting the firm's business objectives. The work spans Java and Spring Boot microservices, Kafka event-driven architectures, Cassandra, AWS data lake and ETL services, and Apache Spark processing. As a core technical contributor, the Lead Software Engineer executes software solutions, produces architecture and design artifacts, and drives team adoption of enterprise-authorized AI-assisted engineering practices.
What you will do
- Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problems
- Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems
- Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards; contributes learnings and reusable patterns to improve broader team effectiveness.
- 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.
- 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
- Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development
- Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems
- Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture
Skills used in this role
What the employer is looking for
- Formal training or certification on software engineering concepts and 5+ years applied experience
- Excellent system design skills for designing distributed systems with scalability, resiliency, security, and performance best practices.
- Advanced proficiency in Java (17/21+) and Spring Boot for building scalable RESTful microservices. Strong command of Kafka for event-driven architectures, including topic design, partitions, consumer groups, and delivery semantics.
- Strong experience in Java (Strong hands-on coding expertise), Spring Boot / Spring Framework, AWS Cloud and Kafka (Deep expertise in event streaming and messaging)
- In-depth knowledge of Cassandra for distributed data modeling, partition strategy, and query tuning at scale.
- Extensive experience with AWS data lake & ETL technologies (S3, Glue, EMR, Lambda, Step Functions) and Maven for build/dependency management.
- Solid expertise in containerization and orchestration using Docker and Kubernetes, deploying workloads on AWS EKS and ECS.
- Hands-on mastery of Apache Spark (batch + streaming) for large-scale data processing and performance optimization. Proven capability in Jenkins-based CI/CD automation, including pipelines, quality gates, artifact publishing, and deployments.
- Effective AI utilization to boost development productivity by leveraging AI agents/skills for coding assistance, test generation, refactoring, documentation, and faster troubleshooting.
- 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
Preferred qualifications
- Familiarity with modern front-end technologies.
- Cassandra, Python
Benefits and support
- Compensation and benefits are detailed in the job posting
About JPMorgan Chase
JPMorgan Chase & Co. is one of the oldest, largest, and most diversified financial services institutions in the world. Operating globally through the J.P. Morgan and Chase brands, the firm provides a comprehensive range of financial solutions including investment banking, consumer and commercial banking, transaction processing, and asset management. Serving millions of consumers and many of the world's most prominent corporate, institutional, and government clients, the company combines deep market expertise with extensive technological investments.
- Industry
- Banking
- Company size
- 320000+ employees
- Founded
- 1799
- Location
- New York, New York, USA
- Funding stage
- Public Company
Leadership
Chairman and Chief Executive Officer
Chief Financial Officer
Chief Operating Officer
Global Chief Information Officer
CEO, Asset & Wealth Management
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