Lead Software Engineer - Java/AWS

JPMorgan Chase & Co.; Kentucky; On-site; USD 140,000 - 190,000; Full time

Job summary

JPMorganChase is seeking a Lead Software Engineer in the SB Lending Tech team within Consumer & Community Banking to drive scalable Java-based services and secure cloud-native solutions on AWS. You will mentor teams, define technical strategies with product partners, and enable analytics workflows with Spark for ML.

You will influence code quality, secure coding, and AI-assisted tooling adoption across teams, balancing performance, reliability, and customer outcomes in a fast-paced setting.

Qualifications

• Formal software engineering training or certification
• 5+ years applied software engineering experience
• Advanced Java with Spring Boot in microservices
• Experience delivering production systems and automated testing
• Cloud-native apps on AWS (compute, storage, DB, containers)
• CI/CD, version control, and pipeline automation
• Automated testing frameworks (JUnit, mocks) and quality focus
• Relational DBs and SQL with performance considerations
• Event streaming knowledge (Kafka)
• Experience using AI-assisted software development tools and secure coding practices
• Responsible AI use and mentoring teams on compliant patterns

Responsibilities

• Lead end-to-end design and delivery of scalable Java services and APIs
• Architect and implement cloud-native AWS solutions
• Mentor engineers through code reviews and design guidance
• Collaborate with product, design, data to improve UX and automate workflows
• Build and optimize data pipelines with Databricks and Spark for analytics/ML
• Drive CI/CD, automated testing, and secure software practices
• Promote AI-assisted engineering practices with measurable validation standards
• Leverage SDLC tools, including AI-assisted development and automation

Skills

Java expertise

Spring Boot

Microservices architecture

AWS cloud

CI/CD pipelines

JUnit testing

SQL databases

Kafka

AI-assisted tooling

Secure coding

Education

Bachelor's degree in CS/CE

Software engineering certification

Tools

Databricks

Apache Spark

Terraform

Kubernetes

Docker

Git

Maven/Gradle

Job description

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 Consumer & Community Banking – SB Lending Tech team, you are an integral part of an agile team that enhances, builds, and delivers secure, stable, and scalable technology products. You will drive meaningful business outcomes by applying deep technical expertise, strong engineering judgment, and a customer-focused mindset to solve complex problems across distributed systems, cloud, and artificial intelligence.

Job responsibilities

• Lead end-to-end design and delivery of scalable Java services and APIs, optimizing for performance, resiliency, and maintainability in production environments
• Architect and implement cloud-native solutions on Amazon Web Services, applying well-structured patterns for reliability, observability, and cost-aware scalability
• Mentor engineers through thoughtful code reviews, design guidance, and pragmatic engineering standards that raise quality and accelerate delivery
• Collaborate with product, design, and data partners to define technical strategies that improve user experience and automate key workflows
• Build and optimize data pipelines using Databricks and Apache Spark to enable analytics and machine learning workflows at scale
• Drive engineering excellence across continuous integration and delivery, automated testing, and secure software development practices
• Drives adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain.
• Applies knowledge of tools within the Software Development Life Cycle toolchain, including approved AI-assisted development and automation capabilities, to improve the value realized by automation at scale.

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience
• Advanced Java experience, including building Spring Boot–based services in a microservices architecture
• Experience with Java (Core & EE, Spring Boot, Spring MVC, Spring Cloud)
• Practical experience delivering system design, application development, automated testing, and operational stability for production systems
• Hands-on experience building cloud-native applications on Amazon Web Services (e.g., compute, storage, database, container, and serverless services)
• Experience with continuous integration and delivery and modern build/version control practices (e.g., Git, Maven/Gradle, and pipeline automation)
• Proficiency with automated testing approaches and frameworks (e.g., JUnit and mocking frameworks) and a strong quality-first mindset
• Experience with relational databases and SQL, including data modeling and performance considerations for high-throughput systems
• Knowledge of messaging and integration patterns, including event streaming technologies such as Kafka
• Demonstrated experience leading effective use of enterprise-authorized AI-assisted software development tools within the work environment (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 senior engineers/leads on compliant usage patterns and controls.

Preferred qualifications, capabilities, and skills

• Basic Python scripting knowledge
• Experience building and deploying agentic or AI-assisted workflows, including evaluation and human-in-the-loop validation patterns
• Experience with infrastructure as code and cloud provisioning automation (e.g., Terraform, CloudFormation, or AWS CDK)
• Experience with containerization and orchestration (e.g., Docker and Kubernetes) for scalable service operations