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# Staff Software Engineer - Fintech AI

- **Company:** CO-RIPPLING LLC
- **Location:** New York, NY, United States
- **Experience:** Expert
- **Salary:** $189,000.0 - $315,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Data Integrity, Distributed Systems, Software Engineering, System Availability, Large Language Models, Backend, Agentic-AI, Build Management, Software Coding
- **Published:** October 5, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=9d6b030139baaec2

## About the Role

* Extensive experience (8+ years) in software engineering, characterized by sustained technical leadership and demonstrating tangible organizational impact.
 * Exceptional depth in architecting platform and distributed systems, specifically in building highly observable and resilient architectures at scale.
 * Uncompromising hands-on coding proficiency, maintaining active contributions to the codebase alongside high-level strategic responsibilities.
 * Proven ability to spearhead cross-functional technical initiatives, driving alignment across integrated engineering and product squads.
 * Acute product intuition, with the capability to transform ambiguous requirements into durable platform primitives and extensible primitives.
 * Precise and articulate communication skills, capable of distilling complex concepts for diverse technical and non-technical stakeholders.
 * Resilience in high-velocity environments where the technical roadmap is continuously evolving alongside emerging technology shifts.
 * Prior expertise in developing agentic workflows or AI-native systems is highly regarded.

## Description

Rippling processes over $40 Billion in payroll annually across 83 countries and the Payroll Onboarding team sits at the absolute centre of this global engine. Every time a new business joins Rippling, our systems are what get them up, running, and compliant.
We are hiring Staff Engineers to redefine how global payroll infrastructure scales. Our mission is to move away from heavy, manual implementation and build a radically automated, self-serve onboarding engine. Right now, that means we are building AI-native onboarding experiences leveraging LLMs to conversationally guide users through dense, regional tax and payroll configurations, while pairing them with deterministic backend systems to guarantee flawless data precision.
Crucially, we aren't just building for today's footprint. We are building the architectural blueprint that accelerates Rippling's expansion into new countries. You will design systems that allow our country expansion teams to spin up payroll in a new market in a fraction of the time, abstracting away local compliance complexities into clean, reusable platform workflows., * Architect for Global Expansion: Design and build platform infrastructure that empowers country expansion teams to deploy Rippling Payroll into new international markets with minimal friction.

 * AI-Driven Workflows: Merge LLMs with rigid, deterministic code. You will build conversational setup experiences that feel human but execute with 100% mathematical and compliance accuracy.
 * Deconstruct Complexity: Translate massive, messy regulatory frameworks and payroll setup flows across dozens of jurisdictions into clean, elegant backend systems and seamless product UX.
 * Scale the Platform: Own core pieces of a massive transactional system, optimizing for scale, high availability, and bulletproof data integrity.

As a Staff Engineer, you will own the architectural blueprint to transform the manual burden into an AI-native product, building self-serve engines that conversationally guide clients through regional tax setup while maintaining 100% precision in the backend.
You will design shared ingestion, reconciliation, and validation primitives not just for today's 40 markets, but crucially to enable country expansion in a fraction of the time it currently takes, abstracting away local compliance complexities into clean, reusable platform workflows., Success requires solving foundational systems problems rather than performing basic model integration:

 * Deterministic Handoffs: Engineering the boundaries where LLMs reason through implementations while maintaining rigid correctness in critical path execution.
 * Agentic Primitives: Defining the specific contracts, tools, and shared abstractions agents utilize for robust payroll data reconciliation.
 * Beyond Accuracy: Designing evaluation frameworks for model output where high probability is insufficient for financial and compliance standards.
 * Risk-Mitigated Velocity: Architecting validation layers and feedback loops that accelerate throughput without compromising system integrity.
 * Global Scalability: Normalizing diverse regional tax laws, statutory filings, and inconsistent provider exports into reusable platform primitives.
 * Operational Control: Sustaining resilient workflows amidst rapid model shifts while strictly managing latency, cost, and overall system quality.