AI Java AWS Lead Software Engineering

JPMorgan Chase & Co.; Columbus (OH); On-site; USD 110,000 - 140,000; Full time

Job summary

JPMorgan Chase & Co. seeks a Lead Software Engineer to join their Consumer & Community Banking Trust and Security Team in Columbus, Ohio. This role involves leading the design and development of secure, cloud-native applications, driving engineering best practices, and mentoring engineers.

The ideal candidate has extensive experience in Java, Spring Boot, and AWS, with a focus on resilience and security in software development. This position promises a dynamic work environment with ample opportunities for technical growth.

Qualifications

• 5+ years of applied experience in software engineering.
• Strong understanding of responsible AI use in engineering workflows.
• Practical experience deploying applications using AWS.

Responsibilities

• Design, develop, and support secure software solutions.
• Lead technical design discussions and contribute to architecture decisions.
• Drive engineering best practices, including CI/CD and secure coding.

Skills

Java

Spring Boot

AWS cloud technologies

Kafka

Software Development Life Cycle

CI/CD

Resiliency testing

Education

Formal training or certification in software engineering

Tools

Kubernetes

AI-assisted development tools

Job description

Make a difference bringing hands‑on leadership in building secure, cloud‑native for our customers.

As a Lead Software Engineer at JPMorganChase within the Consumer & Community Banking Trust and Security 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

• Design, develop, test, deploy, and support secure, scalable, and resilient software solutions using Java, Spring Boot, AWS cloud technologies, and Kafka
• Build and maintain RESTful APIs, microservices, backend services, and event‑driven integrations
• Develop secure, high‑quality production code and review, debug, and improve 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 discussions and contribute to architecture decisions for highly available and maintainable applications
• Troubleshoot complex technical issues across applications, cloud infrastructure, eventing platforms, and integrations
• Identify opportunities to eliminate, automate, or reduce recurring issues to improve operational stability
• Drive engineering best practices, including CI/CD, automated testing, observability, resiliency, secure coding, and production readiness
• Partner with product owners, architects, engineering teams, and stakeholders to deliver solutions aligned to business priorities and control requirements
• Mentor engineers and contribute to a culture of diversity, opportunity, inclusion, and respect

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience
• Strong experience with Java and Spring Boot (8 plus years)
• 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
• Experience designing and building RESTful APIs, microservices, and distributed backend services.
• Practical experience developing, deploying, or supporting applications using AWS cloud technologies
• Experience with Kafka or similar event‑streaming platforms
• Proficient in all aspects of the Software Development Life Cycle
• Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
• Experience developing secure production code, performing code reviews, and improving engineering standards.
• Strong troubleshooting and problem‑solving skills with experience improving production stability.

Preferred qualifications, capabilities, and skills

• Expertise with modern middleware services technologies
• Experience with containerized application delivery and Kubernetes‑based platforms
• Experience with Kafka‑based event‑driven architecture, messaging platforms, or streaming technologies
• Experience with infrastructure‑as‑code or cloud deployment automation
• Experience with performance tuning, resiliency testing, monitoring, logging, and alerting
• Experience working in highly controlled or regulated technology environments
• Experience with security, identity, access, fraud, trust, risk, or customer protection platforms