Principal Software Engineer- Core AI Platform

If you are looking for a game-changing career, working for one of the world's leading financial institutions, you've come to the right place.

As a Principal Engineer at JPMorgan Chase on the Core AI Infrastructure Platform team, you will design and promote the shared ecosystem that unifies our training and inference pipelines across hybrid-cloud and Neo-cloud environments.

If you thrive on solving deep infrastructure challenges, establishing resilient SRE standards, and building foundational tech stack that enables thousands of engineers to safely and efficiently deploy cutting-edge AI models into production, this is your opportunity to shape the future of AI infrastructure at scale.

Job responsibilities


* Architect and Design solutions to enhance the reliability and scalability of AI/ML platforms and applications to accommodate fast-growing demand


* Build and enhance reusable platform services, APIs, SDKs, agents, skills, and libraries that standardize how application teams consume model hosting, inference, and AI/ML managed services


* Partner with AI infrastructure training, inference, and architecture teams to implement AI Foundation Services capabilities that unblock AI use cases, supporting delivery from technical design through build, launch, and early operational support


* Own and evolve non-functional requirements and build/enhance tooling for observability, resilience, security controls, infrastructure management, and cost optimization


* Establish and enforce standards and reference architectures for reliability, observability, automation, and operational readiness across services


* Partner with product and platform engineering teams to define and meet service reliability targets, including performance, availability, and recoverability


* Participate in on-call rotations, debug and resolve complex production issues; identify systemic gaps and drive durable remediation


* Mentor and guide engineers; raise the bar on engineering quality, documentation, and operational rigor

Required qualifications, capabilities, and skills


* Formal training or certification on software engineering concepts and 10+ years applied experience


* Strong hands-on coding experience in Python with experience delivering production-grade services


* 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


* Hands-on practical experience with system design, automated testing, debugging, and operational s...