Staff Software Engineer - Rippling AI

Responsibilities

• Own major AI Platform initiatives across backend, platform, infrastructure, and AI-enabled systems.
• Lead design and execution for systems supporting agents, evaluations, automation, data pipelines, model quality, sandboxing, scaling, latency, and reliability.
• Act as a technical lead for cross-functional work involving Product, Infrastructure, Platform, AI, and Engineering teams.
• Break down ambiguous technical problems into clear architecture and execution plans.
• Write code, review critical code paths, debug production issues, and make implementation-level decisions.
• Build reusable platform systems for multiple product teams.
• Raise the engineering bar through design reviews, code reviews, mentoring, and technical guidance.
• Balance speed, quality, reliability, and long-term platform maintainability.

Requirements

• 10–15 years of software engineering experience, preferably in backend, platform, infrastructure, distributed systems, AI platform, or product engineering.
• Strong hands-on coding ability and willingness to remain close to code, debugging, design reviews, and implementation details.
• Strong programming knowledge in one or more languages such as Python, Java, Go, C++, Scala, Kotlin, or C#.
• Proven experience building and operating large-scale distributed systems in production.
• Experience in high-growth or hyper-growth startup or product environments is strongly preferred.
• Strong system design and architecture fundamentals across APIs, databases, data modeling, concurrency, reliability, observability, and production operations.
• Ability to lead ambiguous, cross-functional technical initiatives without formal authority.
• Strong product intuition and ability to connect technical decisions to customer and business impact.
• Ability to mentor engineers and raise the technical bar while continuing to code.
• Practical exposure or strong curiosity around AI agents, LLM infrastructure, agentic workflows, ML/data infrastructure, inference pipelines, evaluations, fine-tuning, post-training, or automation systems.

Nice-to-haves

• Recent hands-on experience building AI agents, LLM tooling, AI infrastructure, automation platforms, evaluation systems, or model-quality systems.
• Experience with workflow orchestration, background automation, self-healing systems, reliability platforms, or internal developer platforms.
• Experience with permissions, approvals, auditability, compliance, security-sensitive workflows, or enterprise-grade controls.
• Strong Python and SQL knowledge.
• Experience with Go, Java, C++, or Scala in platform, infrastructure, distributed systems, or large-scale backend environments.
• Experience in AI-native, cloud/infrastructure, platform-heavy, enterprise SaaS, fintech, HR technology, payroll, benefits, compliance, IT, or workflow-heavy companies.