6 days ago
Responsibilities
- Own broad, ambiguous AI Platform technical charters across multiple systems and teams.
- Lead architecture and execution for foundational systems supporting AI capabilities across Rippling product areas.
- Build and guide AI platform infrastructure, harness engineering, evaluation frameworks, model-related infrastructure, sandboxing, scaling, latency, and reliability work.
- Write code, review critical code paths, debug complex production issues, prototype solutions, and make implementation-level decisions.
- Partner with Product, Infra, Platform, AI, and senior engineering stakeholders to turn ambiguous AI and product bets into scalable systems.
- Lead without formal authority, mentor Staff, Senior, and SE II engineers, and raise engineering standards.
- Define reusable technical patterns and platform primitives and help shape Rippling AI’s long-term technical foundation.
Requirements
- 12+ years of software engineering experience, depending on scope and impact.
- Strong backend, platform, infrastructure, distributed systems, or systems engineering foundation.
- Deep hands-on coding ability and regular experience designing, reviewing, debugging, and writing code.
- Strong programming knowledge in one or more of Python, Java, Go/Golang, C++, Scala, Kotlin, or C#.
- Experience owning broad, ambiguous technical charters across multiple systems or teams.
- Strong architecture and system design depth across large-scale production systems.
- Strong technical judgment across scale, reliability, latency, observability, APIs, data modeling, concurrency, and production operations.
- Ability to operate as a builder-leader, influence without formal authority, connect technical decisions to business and customer impact, and mentor engineers.
- AI/ML background is preferred but not mandatory; practical exposure to AI platform infrastructure, agents, evaluation systems, ML/data infrastructure, model infrastructure, inference, sandboxing, workflow automation, scaling, latency, or reliability is valuable.
- Preferred qualifications include AI platform infrastructure, evaluation frameworks, harness systems, LLM tooling, model-quality systems, ML/data infrastructure, sandboxing, inference systems, latency optimization, reliability engineering, internal platforms, high-growth technology companies, or enterprise SaaS and fintech environments.
- Strong Python and SQL knowledge and experience with Go, Java, C++, or Scala in backend, infrastructure, platform, or distributed systems environments are preferred.
Benefits
- Competitive salary, benefits, and equity are provided.
- Office-based employees within a defined radius are currently expected to work in the office at least three days per week.
- Reasonable accommodations are available for candidates with disabilities during the hiring process.
About Rippling
Rippling builds a unified workforce management platform that combines HR, payroll, IT, and finance software for businesses on a single system. Its SaaS suite covers onboarding, payroll, time tracking, benefits, device and identity management, spend/expenses, and accounting integrations with ERPs like NetSuite, QuickBooks, Microsoft Dynamics 365, and Oracle. Founded in 2016 and headquartered in San Francisco, Rippling is privately held and serves companies from startups to large enterprises.