Staff Software Engineer – AI-Driven Global Payroll Platform

rippling; San Francisco (CA); On-site; USD 180,000 - 260,000; Full time

Job summary

Rippling is seeking Staff Engineers to redefine how global payroll infrastructure scales. You will architect platform infrastructure and AI-native onboarding experiences to automate regional tax setup and payroll configurations.

You will design reusable platform workflows to expand into new countries, ensuring data integrity across markets while balancing speed, compliance, and cost for a scalable, observable system.

Qualifications

• 8+ years in software engineering with leadership experience.
• Deep expertise in platform and distributed systems.
• Hands-on coding with active contributions to codebase.
• Proven ability to drive cross-functional technical initiatives.

Responsibilities

• Architect for Global Expansion: design and build platform infrastructure for deploying Rippling Payroll into new international markets with minimal friction.
• AI-Driven Workflows: merge LLMs with deterministic code to create conversational onboarding experiences with 100% accuracy.
• Deconstruct Complexity: translate regulatory frameworks into clean backend systems and seamless UX.
• Scale the Platform: own core pieces of a massive transactional system for high availability and data integrity.
• Own onboarding primitives: design shared ingestion, reconciliation, and validation workflows for multi-market expansion.

Skills

Software architecture

Distributed systems

Leadership

Hands-on coding

Cross-functional collaboration

Education

Bachelor's degree in Computer Science or related field

Tools

AWS

GCP

LLMs

Job description

Rippling is seeking Staff Engineers to redefine how global payroll infrastructure scales. You will architect platform infrastructure and AI-native onboarding experiences to automate regional tax setup and payroll configurations.

You will design reusable platform workflows to expand into new countries, ensuring data integrity across markets while balancing speed, compliance, and cost for a scalable, observable system.