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 JPMorgan Chase within the Infrastructure Platforms team, 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.

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
Build and operate cloud-native solutions using Kubernetes with strong systems fundamentals, on at least one cloud provider (AWS / GCP / Azure)
Develop services primarily in Golang and/or Java (either or both)
Produce secure, high-quality production code aligned to engineering best practices
Review and debug code written by others while enforcing consistent validation standards (secure coding, peer review, automated testing)
Drive consistent validation practices across the team to improve overall code quality and delivery outcomes
Promote reuse of effective patterns and scalable approaches across the team to improve engineering efficiency
Identify and implement opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability, and lead evaluation sessions with external vendors/startups and internal teams to assess architectural designs and technical fit within existing systems and information architecture
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
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
Hands-on practical experience delivering system design, application development, testing, and operational stability
Advanced in one or more programming language(s)
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
Practical cloud native experience

Preferred qualifications, capabilities, and skills

Spec Drive Development (SDD) experience is a plus
Strong AI tool usage fluency (comfortable leveraging AI tools in day-to-day engineering workflows)
Prior understanding of Cloud Governance is a plus

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