Lead Software Engineer-AI Foundation Services

Join JPMorganChase's Chief Data & Analytics (AIML Data Platforms) team in Jersey City as a Lead Software Engineer building AI foundation services for GenAI and ML at enterprise scale.

You'll lead hands-on delivery of secure, reliable, cloud-native platform capabilities (Kubernetes/CI/CD/IaC) and partner with application teams to create reusable integrations, reference implementations, and onboarding assets.

As a Lead Software Engineer at JPMorganChase within the AIML Data Platforms - Chief Data and Analytics 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.

In this role you will get to drive significant business impact through your capabilities and contributions and apply your deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications.

Job responsibilities



* Partners with Lines of Business application teams to implement AI Foundation Services capabilities that unblock GenAI/AI use cases, supporting delivery from technical design through build, launch, and early operational support


* Builds and enhances reusable platform services, APIs, SDKs, and libraries that standardize how application teams consume model hosting, inference, and AI/ML managed services


* Translates functional and non-functional application requirements into clear technical designs, engineering tasks, and delivery milestones with support from senior engineers and architects


* Develops secure, stable, and high-quality production code, and participates in code reviews, debugging, testing, and remediation of defects across AI Foundation Services components


* Creates and maintains reusable engineering assets such as reference implementations, runbooks, test harnesses, baseline configurations, and onboarding guides to accelerate adoption across teams


* 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.


* Designs and implements scalable software components using appropriate software design patterns, cloud-native practices, and platform engineering standards


* Collaborates with cross-functional teams across product, architecture, security, infrastructure, and application development to resolve technical dependencies and deliver producti...