Salary context
Typical pay for US Software Engineer Jobs roles in Jersey City: $120k–$196k (median $177k).
Based on 6 live listings with disclosed salary.
Description
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