Lead Software Engineer - Investment Portfolio Technology

JPMorgan Chase & Co.; Jersey City (NJ); On-site; USD 140,000 - 190,000; Full time

Job summary

JPMorgan Chase & Co. in Jersey City, NJ seeks a Lead Software Engineer within the Asset Management Technology organization to design and deliver secure, scalable platforms powering CMAS and SMA investments at retail scale.

You will lead end-to-end delivery, mentor teams, and collaborate with Product, Business, and Operations to translate requirements into robust software. You will embed responsible AI usage, drive production readiness, and raise engineering standards across teams while guiding

Qualifications

• Formal training or certification on software engineering concepts.
• Advanced knowledge of application, data, and infrastructure architecture.
• Hands-on practical experience delivering platform/system design, application development, performance testing, incident management and operational stability.
• Advanced in one or more programming language(s) - Java and Python.
• Demonstrated experience leading effective use of approved AI-assisted software development tools with the ability to set team expectations for validating AI outputs.
• Strong understanding of responsible AI use in engineering workflows and secure handling of inputs/outputs.
• Proficient in all aspects of the Software Development Life Cycle and agile methodologies such as CI/CD.
• Experience building RESTful web services, microservices, API design, testing, performance tuning, and secure coding.
• Strong AWS experience with production-grade services and patterns.
• Strong experience designing and operating data solutions in Snowflake.
• Strong SQL skills; experience with stored procedures.

Responsibilities

• Design, build, test, and deploy Java-based microservices and REST APIs; lead delivery across multiple services by driving execution and aligning to guardrails.
• Build and evolve data pipelines and curated datasets for trading, reporting, and controls; ensure data governance and auditability.
• Own production readiness, observability, resiliency, incident response, and post-incident improvements.
• Embed security, resiliency, and controls into design and implementation; maintain coding standards and release governance.
• Partner with stakeholders to translate business outcomes into technical delivery plans and lead engineering in agile planning.
• Foster inclusion and raise engineering standards through code reviews and best practices.
• Model safe AI-assisted development practices and ensure validation of AI outputs.

Skills

Java

Python

AI-assisted tools

Cloud AWS

REST APIs

CI/CD

Security & Resiliency

Snowflake data

SQL

Agile methodologies

Leadership

Education

Software engineering certification

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 (AM) Technology organization, 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.

This is an exciting opportunity to join a passionate team dedicated to building products that truly help our users. As a Lead Software Engineer within AM Technology, you will be a hands-on engineer responsible for designing and delivering secure, resilient, and scalable platforms that power Customized Managed Account Solutions (CMAS) investing and Separately Managed Accounts (SMA) at retail scale. You will lead key components end-to-end (design, delivery, production stewardship) and partner closely with Product, Business, and Operations stakeholders. You will lead through technical direction, deep delivery ownership, and raising engineering standards across teams.

Job responsibilities

• Design, build, test, and deploy Java-based microservices and REST APIs (with Python where appropriate) supporting SMA trading, data workflows, and client servicing; lead delivery across multiple services/teams by driving execution, managing dependencies and trade-offs, enforcing alignment to established architecture/engineering guardrails, and continuously improving standards and practices through code reviews and adoption of proven industry best practices.

• Build and evolve data pipelines and curated datasets used for trading, client reporting, operational insights, and controls; partner with data governance, risk, and controls stakeholders to ensure lineage, quality, access controls, and auditability; drive Snowflake best practices (performance, cost controls, secure data sharing patterns, environment hygiene).

• Own production readiness (observability, resiliency, incident response, post-incident improvements); eliminate recurring issues through automation and platform fixes; establish SLOs/error budgets; support production as needed and ensure rapid triage/root-cause resolution.

• Embed security, resiliency, and controls into design and implementation; ensure adherence to IT control policies and corporate standards; raise the bar on code reviews, testing strategy, release governance, and documentation quality.

• Partner continuously with stakeholders to translate business outcomes into technical delivery plans; participate in agile planning and provide engineering leadership on scope, sequencing, and delivery risk.

• Foster a culture of inclusion, continuous learning, experimentation, and high engineering standards through design reviews, operational leadership, and engineering best practices.

• Model safe and effective use of enterprise-authorized AI-assisted development tools (coding, tests, troubleshooting, documentation), including validation expectations and secure handling of sensitive inputs/outputs.

• Drive 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

• Formal training or certification on software engineering concepts and 5+ years applied experience

• Advanced knowledge of application, data, and infrastructure architecture

• Hands-on practical experience delivering platform/system design, application development, performance testing, incident management and operational stability

• Advanced in one or more programming language(s) - Java and Python

• 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 practice

• Proficient in all aspects of the Software Development Life Cycle and advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security

• Experience building RESTful web services, microservices, API design, testing, performance tuning, and secure coding.

• Strong AWS experience with production-grade services and patterns.

• Strong experience designing and operating data solutions in Snowflake (schema design, performance, secure access, operationalization).

• Strong SQL skills; experience with stored procedures and relational concepts.

Preferred qualifications, capabilities, and skills

• AWS certification(s) - Developer, Solutions Architect, ML Engineer, AI Developer, DevOps Engineer, CloudOps Engineer

• Airflow (or equivalent orchestration) experience

• Modern CI tooling experience - GitHub, BitBucket, GitLab, Jenkins, etc.

• Financial Services experience and familiarity with trading concepts/trade lifecycle.