Lead Software Engineer - Quantitative Portfolio Construction Development

JPMorgan Chase & Co.; New York (NY); On-site; USD 170,000 - 230,000; Full time

Job summary

JPMorgan Chase & Co. in New York, NY, seeks a Lead Software Engineer to drive design, development, and delivery of scalable, secure market-leading technology for Asset Management Technology.

You will contribute as a core technical contributor across multiple areas, collaborating with stakeholders to translate business needs into robust software solutions. The role emphasizes hands-on coding in Java/Python, cloud-native delivery on AWS, and leadership in implementing AI-assisted engineering

Qualifications

• 5+ years of software engineering experience.
• Hands-on design, development, testing, and operational stability.
• Proficiency in Python or Java; production code experience.
• Cloud native experience with AWS and IaC (Terraform).
• Experience leading AI-assisted development practices and code reviews.

Responsibilities

• Develop secure, high-quality production code and review others' code.
• Solve complex technical problems beyond routine approaches.
• Lead AI-assisted engineering practices to improve quality and delivery speed.
• Work across SDLC tools to improve automation and reliability.
• Identify and automate recurring issues to enhance stability.
• Lead architecture and design evaluation sessions with stakeholders.

Skills

Java / Python proficiency

Agile methodologies

SDLC mastery

Leadership & collaboration

Tools

AWS (S3, EC2, EMR)

Terraform

CI/CD tooling

AI-assisted dev tools

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 the Asset Management Technology, 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.

JPMorgan Asset Management Technology is seeking a well-rounded hands-on quantitative developer that is experienced in building systems that support the full investment management cycle. Tech stack focus is Java and/or Python. The candidate will be part of the front-office technology team and have good business knowledge and communication skills to work with the stakeholders and develop functional specifications. The candidate will be joining a high-performance, award-winning team who build applications that support the investment management cycle including research, portfolio management and investment.

Job responsibilities

• Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problems
• Develops secure and high-quality production code, and reviews and debugs 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.
• Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
• Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience
• Hands-on practical experience delivering system design, application development, testing, and operational stability
• Advanced in one or more programming languages (e.g., Python or Java) and experience developing, debugging, and maintaining production code.
• Practical cloud native experience.Hands-on experience with Amazon Web Services (AWS) services and cloud delivery practices, including infrastructure as code (e.g., Terraform) and services such as Amazon Simple Storage Service (Amazon S3), Amazon Elastic Compute Cloud (Amazon EC2), and Amazon EMR.
• 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
• Proficient in all aspects of the Software Development Life Cycle
• 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 with distributed data processing using Spark and modern data platforms (e.g., Databricks).
• Proficiency in data engineering and platform development.
• Experience with relational databases (e.g., Oracle) and/or cloud data platforms, including performance tuning and query optimization.
• Strong analytical skills to support data understanding, quality investigation, and reporting use cases.
• Knowledge of banking and financial services domain concepts relevant to data processing and reporting.