Lead Software Engineer - Java

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As a Lead Software Engineer at JPMorganChase within the Consumer & Community Banking, 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 break down technical problems

- Develops secure 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.

- 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

- Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies

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

- Strong hands-on experience in Java backend development and Spring Boot in production environments

- Proven ability in system design for scalable, secure services using microservices and API-driven architectures

- Strong engineering fundamentals including object-oriented programming, design patterns, concurrency, debugging, and performance tuning

- Solid testing discipline encompassing unit and integration testing, automation, and code quality practices

- Advanced proficiency in programming languages (Java, Python, C#, etc.), Hands-on work with Large Language Models (LLMs) and generative AI.

- Experience with distributed systems and cloud platforms (AWS, GCP, Azure).

- Expertise in microservices, RESTful APIs, and database technologies (relational/NoSQL) and experience with development and testing tools and frameworks (JUnit, UDF, Tophat, Cucumber , Groovy, Postman, REST Assured, Eclipse, Maven, Jenkins, IntelliJ).

- Experience with performance testing tools (JMeter, Blazemeter) and Chaos Monkey Testing.

Preferred qualifications, capabilities, and skills:

- Cloud certification (AWS, GCP, Azure).

- Practical public cloud development experience.

- In-depth knowledge of the financial services industry and their IT systems.

- Wealth Planning tool experience

- Effective communication across teams and management, with a proactive approach to process improvement.

- Strong system design, application development, and operational stability skills.

- Familiarity with AI/ML frameworks (PyTorch, scikit-learn, Hugging Face).