Lead Software Engineer - Java, Python preferred

JPMorgan Chase & Co.; Columbus (OH); On-site; USD 140,000 - 190,000; Full time

Job summary

JPMorganChase seeks a Lead Software Engineer in its Asset & Wealth Management division to raise engineering standards through hands-on development, thoughtful design, and mentorship that helps the team grow.

You will own end-to-end delivery of secure services and APIs, partnering with product and engineering peers across regions to solve complex business and technical problems with speed, safety, and reliability.

Qualifications

• 5+ years hands-on software engineering with design, development, testing, and operations.
• Delivering system design, application development, testing, and operational stability.
• Strong Java with Spring Boot and REST API experience.
• Data modeling skills and strong SQL proficiency.
• Automation and CD/CI expertise; end-to-end SDLC knowledge.
• Advanced Agile engineering practices including CI/CD, resilience, security.
• Experience with AI-assisted development tools and safe adoption.
• Awareness of responsible AI use and secure handling of data outputs.

Responsibilities

• Execute creative software solutions as a senior developer on a strategic client reporting platform.
• Engineer data pipelines, calculations, data distribution and client reporting.
• Develop secure, high-quality production code and mentor junior developers.
• Deliver solutions as part of an Agile Scrum team and participate in ceremonies.
• Collaborate with manager/Product Owner to use metrics for team improvement.
• Communicate with end users and POs to align work with business goals.
• Collaborate with Scrum teams regionally to share solutions and best practices.
• Identify opportunities to automate remediation for stability and reliability.
• Promote enterprise AI-assisted practices with secure validation standards.

Skills

Java

Spring Boot

REST API

SQL

CI/CD

Agile

Cloud

AI-assisted tools

Secure coding

Data modeling

Job description

You will raise engineering standards through hands-on development, thoughtful design, and mentorship that helps the team grow.

As a Lead Software Engineer at JPMorganChase within Asset & Wealth Management, you will build and evolve modern platform capabilities that help advisors, clients, and operations teams deliver outcomes with speed, safety, and reliability. You will own end-to-end delivery of secure services and APIs, partnering closely with product and engineering peers across regions to solve complex business and technical problems.

Job responsibilities

• Execute creative software solutions across design, development, and technical troubleshooting working as a senior developer individual contributor on a strategic client reporting and data platform.
• Engineer data pipelines, calculations, data distribution and reporting to be presented to Asset Management clients.
• Develop secure, high-quality production code, and mentor junior developers through code reviews, design sessions and knowledge sharing.
• Deliver technology solutions as part of an Agile Scrum team, contributing to sprint planning, complexity analysis, daily standups, and retrospectives to drive predictable outcomes.
• Partner with manager and Product Owner to use metrics to continuously improve practices to build a high performing team.
• Work directly with end users and Product Owners to communicate status, understand requirements, and ensure an understanding of how work aligns with business objectives.
• Collaborate with Scrum teams locally and across regions to share solutions, challenges, and best practices, improving consistency and delivery speed.
• Identify opportunities to eliminate or automate remediation of recurring issues to improve operational stability and service reliability.
• 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.

Required qualifications, capabilities and skills

• Strong software engineering practices and 5+ years applied hands on experience.
• Track record of hands-on practical experience delivering system design, application development, testing, and operational stability.
• Strong Java skills with demonstrated Spring Boot and REST API development experience.
• Applied knowledge in data modeling and strong SQL skills.
• Proficiency in automation and continuous delivery methods (CI/CD).
• Proficiency across the Software Development Life Cycle, from design through build, test, release, and support.
• Advanced understanding of Agile engineering practices including continuous integration and delivery, application resiliency, and security.
• Demonstrated proficiency in software applications and technical processes within a technical discipline (for example, cloud, artificial intelligence, machine learning, or mobile).
• 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, capabilities and skills

• Experience building cloud-native solutions on Amazon Web Services.
• Python knowledge or a desire to learn independently.
• Knowledge of data pipeline tools such as PySpark, Snowflake, or Databricks.
• Financial services knowledge, with an understanding of how technology enables Asset & Wealth Management products and client experiences.