Lead Software Engineer - Infrastructure Platforms

JPMorganChase•Plano, TX

15h

About The Position

As a Lead Software Engineer on JPMorganChase’s Infrastructure Platforms team, you will work as an integral member of an agile team to enhance, build, and deliver secure, stable, scalable, market-leading technology products. You will use deep technical expertise and problem-solving skills to address challenges across multiple technologies and applications and drive meaningful business impact. The role provides technical direction to business and technology teams, contractors, and vendors; develops and reviews production code; and influences product design, application functionality, and technical operations. It also leads adoption and governance of approved AI-assisted engineering practices, with measurable validation standards for security, correctness, testing, and operational outcomes. You will apply Software Development Life Cycle (SDLC) toolchain capabilities to improve automation at scale and contribute to the engineering community by advocating firmwide frameworks, tools, and practices.

Requirements

Formal training or certification in software engineering concepts and at least 5 years of applied experience.
Hands-on practical experience delivering system design, application development, testing, and operational stability.
Advanced proficiency in one or more programming languages.
Demonstrated experience leading effective use of enterprise-authorized AI-assisted software development tools, such as for coding, code review, test acceleration, or troubleshooting.
Ability to establish team expectations for validating AI outputs for correctness, performance, and security.
Strong understanding of responsible AI use in engineering workflows, including data sensitivity, secure handling of inputs and outputs, and adherence to resiliency and security expectations.
Ability to coach senior engineers and leads on compliant AI usage patterns and controls.
Ability to independently address design and functionality problems with little to no oversight.
Practical cloud-native experience.

Nice To Haves

Experience in infrastructure architecture designs, Kubernetes, CNI, CSI, CRI, and containers.
Experience with AWS EKS and GCP GKE ecosystems.
Knowledge of industry-wide technology trends and best practices.
Knowledge of multiple cloud platforms.
Proficiency in database technologies such as Oracle, MS SQL, or Cockroach.

Responsibilities

Provide technical guidance and direction to the business, technical teams, contractors, and vendors.
Develop secure, high-quality production code and review and debug code written by others.
Drive adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes.
Establish measurable validation standards for AI-assisted work, including secure coding, peer review, and automated testing, and promote reuse of proven patterns and automation within the SDLC/TLM toolchain.
Apply tools in the Software Development Life Cycle toolchain, including approved AI-assisted development and automation capabilities, to improve the value of automation at scale.
Drive decisions affecting product design, application functionality, and technical operations and processes.
Serve as a function-wide subject matter expert in one or more areas of focus.
Contribute to the engineering community by advocating firmwide SDLC frameworks, tools, and practices.
Set team expectations for validating AI outputs for correctness, performance, and security.
Coach senior engineers and leads on compliant AI usage patterns and controls.