Lead Software Engineer - Infrastructure Platforms

JP Morgan Chase; Plano (TX); On-site; USD 150,000 - 190,000; Full time

Job summary

JPMorganChase is seeking a Lead Software Engineer to join the Infrastructure Platforms team in a fast-paced, agile environment. You will guide cross-functional teams, write secure production code, and shape decisions that affect product design and operational stability.

You will advocate responsible AI usage, harness AI-assisted tooling for coding and testing, and help ensure delivery speed and quality across multiple technologies and applications.

Qualifications

• Formal training or certification on software engineering concepts and 5+ years applied experience.
• Advanced in one or more programming language(s).
• Experience leading effective use of enterprise-approved AI-assisted software development tools with guidance on validating AI outputs.

Responsibilities

• Regularly provides technical guidance to support the business and its teams, contractors, and vendors.
• Develops secure and high-quality production code, and reviews and debugs code written by others.
• Drives adoption and governance of AI-assisted engineering practices across teams with measurable validation standards and automation reuse.

Skills

Advanced programming

AI-assisted tools

Independent problem solving

Cloud-native experience

Education

Software engineering training

Tools

Kubernetes

AWS

GCP

CI/CD tooling

Job description

Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products.

As a Lead Software Engineer at JPMorganChase 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. Drive significant business impact through your capabilities and contributions, and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications.

Job responsibilities:

• Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendors
• Develops secure and high-quality production code, and reviews and debugs code written by others
• Drives adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain.
• Applies knowledge of tools within the Software Development Life Cycle toolchain, including approved AI-assisted development and automation capabilities, to improve the value realized by automation at scale.
• Drives decisions that influence the product design, application functionality, and technical operations and processes
• Serves as a function-wide subject matter expert in one or more areas of focus
• Actively contributes to the engineering community as an advocate of firmwide frameworks, tools, and practices of the Software Development Life Cycle

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 enterprise-authorized AI-assisted software development tools within the work environment (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 senior engineers/leads on compliant usage patterns and controls.
• Ability to tackle design and functionality problems independently with little to no oversight
• Practical cloud native experience

Preferred qualifications, capabilities, and skills:

• Experience in Infrastructure Architecture designs, Kubernetes, CNI, CSI, CRI and Containers
• Experience in AWS EKS, GCP GKE ecosystems a plus
• Knowledge of industry-wide technology trends and best practices
• Knowledge of multiple Cloud Platforms
• Proficiency in database technology such as Oracle / MS SQL / Cockroach