Lead Software Engineer - Full Stack | Wealth Management Tech - Digital & Client Services
Confirmed on the employer's own hiring board on Oct 25, 2026. First seen by Alion on Aug 21, 2026. JPMorganChase scores A on the Alion truth index.
This is an exciting opportunity to join a passionate team dedicated to building products that truly help our users.
As a Senior Lead Software Engineer at JPMorgan Chase within Asset Wealth Management, you’ll work with cutting-edge technologies in a collaborative, diverse, and innovative environment, tackling complex challenges and driving impactful solutions for our clients. JPMorgan Asset Management offers a broad range of investment strategies and operates in major markets worldwide, with a clear focus on managing client assets and delivering strong risk-adjusted returns.
Job responsibilities
Design, develop, and maintain innovative software solutions for the JP Morgan Chase Client Services Platform, addressing complex technical challenges and modernizing business processes
Write secure, high-quality production code in Java, Spring, and React; review and debug code from team members to uphold best practices.
Advance the use of AI technologies to improve software development, automation, and operational efficiency.
Lead hands-on system design, application development, testing, and ensure ongoing operational stability.
Build and deploy scalable architecture and solutions on Cloud
Utilize SQL and Snowflake for effective data management, querying, reporting and data sharing
Take initiative in daily tasks and project work, driving progress and innovation within a small, agile team.
Collaborate directly with Product Owners & Global stakeholders to gather requirements and deliver high-impact solutions.
Serve as the primary point of contact for product-related matters, facilitating communication between teams, with high degree of accountability
Solve technical and business challenges efficiently, proactively addressing issues to support Asset Management reporting and delivery.
Required qualifications, capabilities, and skills
Formal training or certification on software engineering concepts and 5+ years applied experience
Hands-on practical experience across the Full Stack Software Development Life Cycle, including system design, application development, testing, and operational stability
Proficiency in core Java and front-end UI frameworks (e.g. JS, React, Angular) for full stack development with demonstrated experience building and maintaining production-grade applications
Strong proficiency in SQL for data querying, transformation, and analysis across large, complex financial datasets
Practical experience working with cloud technologies (AWS)
Solid Knowledge of deployment processes, including experience with GIT and version control systems.
Hands-on practical experience delivering system design, application development, testing, and operational stability
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
Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
In-depth knowledge of the financial services industry and their IT systems
Preferred qualifications, capabilities, and skills
Experience in the financial services industry
Expertise in designing, implementing, and managing cloud-based solutions using AWS, ensuring scalability, reliability, and security for applications.
Familiarity with observability tools such as Splunk, Dynatrace, or Grafana.
Hands-on experience with GraphQL for efficient data querying and integration.
Experience working with data platforms such as Snowflake or Databricks.
Experience in Kafka messaging