Lead AI Platform Reliability Engineer

JPMorgan Chase

Seattle (WA)

On-site

USD 157,000 - 215,000

Full time

14 days+

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Job summary

JPMorganChase in Seattle is seeking a Lead Software Engineer to drive reliability and scalability of AI/ML platforms, delivering secure, production-ready services and reusable tooling. You will mentor engineers, participate in on-call rotations, and partner with product teams to meet reliability targets while advancing observability, security, and cost optimization across the platform.

This role requires strong Python coding, cloud experience, and a collaborative mindset with cross-functional

Qualifications

5+ years of applied experience in software engineering.
Strong Python production-grade coding experience.
Experience leading AI-assisted development tools and validating outputs.
Understanding of responsible AI, data handling, and security expectations.
Hands-on design, testing, debugging, and production stability.
Experience with observability, logging, metrics, and incident response.
Ability to break down requirements and deliver milestones with cross-functional teams.
Excellent written and verbal communication.

Responsibilities

Design and implement solutions to enhance the reliability and scalability of AI/ML platforms and applications to accommodate fast-growing demands.
Develop secure, stable, and high-quality production code, and participate in code reviews, debugging, testing, and remediation of defects across AI Foundation Services components.
Build and enhance reusable platform services, APIs, SDKs, and libraries that standardize how application teams consume model hosting, inference, and AI/ML managed services.
Partner with Lines of Business application teams to implement AI Foundation Services capabilities that unblock generative AI and 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.