Join Rippling, a leader in unifying HR, IT, and Finance for businesses. We empower companies to manage their entire employee lifecycle from a single platform, from onboarding new hires in 90 seconds to managing payroll, benefits, and IT.

We are building core AI capabilities and the foundational AI Platform that will power innovation across all of Rippling's product areas, including Payroll, Benefits, HR, Talent, Spend, IT, and Data Cloud. This is an opportunity to shape the future of AI within a fast-growing SaaS company.

Rippling is based in San Francisco, CA, and has secured significant funding from top investors. We've been recognized as one of America's best startup employers.

As a Senior Staff Software Engineer, you will take ownership of ambitious, high-impact technical initiatives within our AI Platform. Your responsibilities will span critical areas such as harness engineering, evaluation frameworks, model infrastructure, sandboxing, scaling, latency optimization, and reliability.

You will lead architectural design and execution for foundational systems that underpin AI capabilities across Rippling. This includes writing and reviewing code, debugging complex production issues, and prototyping solutions. You'll collaborate closely with Product, Infra, Platform, and AI teams to translate AI and product visions into robust, scalable systems. Mentoring engineers and defining reusable technical patterns will also be key aspects of this role, helping to elevate our engineering standards and shape the long-term technical vision for Rippling AI.

We seek exceptionally strong, hands-on engineers with a deep backend, platform, infrastructure, distributed systems, or systems engineering foundation. A minimum of 14 years of software engineering experience, judged by scope and impact, is required.

Candidates must possess proven experience in owning broad, ambiguous technical charters across multiple systems or teams, demonstrating strong architectural and system design depth for large-scale production environments. Excellent technical judgment in areas like scale, reliability, latency, observability, APIs, data modeling, concurrency, and production operations is essential.

Proficiency in one or more programming languages such as Python, Java, Go, C++, Scala, Kotlin, or C# is necessary. The ability to influence and lead without formal authority, coupled with high intellectual horsepower, rapid learning ability, and comfort in ambiguity, is highly valued. While an AI/ML background is a plus, strong adjacent experience in AI platform infrastructure, model infrastructure, or related fields is highly desirable.