Staff Software Engineer - Fintech AI

$189K - $315K New York, NY, US Senior AI Software Engineer

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Skills & Technologies

Bedrock

About This Role

AI job market dashboard showing open roles by category

About Rippling

Rippling gives businesses one place to run HR, IT, and Finance. It brings together all of the workforce systems that are normally scattered across a company, like payroll, expenses, benefits, and computers. For the first time ever, you can manage and automate every part of the employee lifecycle in a single system.

Take onboarding, for example. With Rippling, you can hire a new employee anywhere in the world and set up their payroll, corporate card, computer, benefits, and even third-party apps like Slack and Microsoft 365—all within 90 seconds.

Based in San Francisco, CA, Rippling has raised $1.4B+ from the world’s top investors—including Kleiner Perkins, Founders Fund, Sequoia, Greenoaks, and Bedrock—and was named one of America's best startup employers by Forbes.

We prioritize candidate safety. Please be aware that all official communication will only be sent from @Rippling.com addresses.

About the role

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.What you will do

  • 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.The Technical Engineering Challenge

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.

What you will need

  • 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.

Additional Information

Rippling is an equal opportunity employer. We are committed to building a diverse and inclusive workforce and do not discriminate based on race, religion, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, age, sexual orientation, veteran or military status, or any other legally protected characteristics, Rippling is committed to providing reasonable accommodations for candidates with disabilities who need assistance during the hiring process. To request a reasonable accommodation, please email [email protected]

Rippling highly values having employees working in-office to foster a collaborative work environment and company culture. Rippling considers working in the office, at least three days a week under current policy, to be an essential function of the employee's role.

This role will receive a competitive salary + benefits + equity. The salary for US-based employees will be aligned with one of the ranges below based on location; see which tier applies to your location here.

A variety of factors are considered when determining someone’s compensation–including a candidate’s professional background, experience, and location. Final offer amounts may vary from the amounts listed below.

The pay range for this role is:

189,000 - 315,000 USD per year(US San Francisco Bay Area)

189,000 - 315,000 USD per year(US Tier 1)

Salary Context

This $189K-$315K range is above the 75th percentile for AI Software Engineer roles in our dataset (median: $192K across 198 roles with salary data).

Role Details

Company Rippling
Title Staff Software Engineer - Fintech AI
Location New York, NY, US
Category AI Software Engineer
Experience Senior
Salary $189K - $315K
Remote No

About This Role

AI Software Engineers build the applications and systems that AI models run inside. They own the API layers, data pipelines, frontend integrations, and infrastructure that turn a model into a product users interact with. Every AI company needs engineers who can build the software around the AI.

The challenge is building reliable systems around inherently unreliable components. Models are probabilistic. They'll give different answers to the same question. They hallucinate. They're slow. They're expensive. Your job is to build an application layer that handles all of this gracefully while delivering a product that users trust and enjoy.

Across the 9,079 AI roles we're tracking, AI Software Engineer positions make up 5% of the market. At Rippling, this role fits into their broader AI and engineering organization.

AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.

What the Work Looks Like

A typical week includes: building API endpoints that serve model inference with caching and fallback logic, designing the data pipeline that feeds context to a RAG system, implementing streaming responses in the frontend, debugging a race condition in the async inference pipeline, and optimizing database queries for the vector search layer. It's full-stack engineering with AI at the center.

AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.

Skills Required

Bedrock (2% of roles)

Full-stack engineering skills with AI integration experience. Python and TypeScript are the most common requirements. You'll need to understand API design, database architecture, and how to build reliable systems around probabilistic outputs. Experience with streaming, async processing, and caching patterns is increasingly important as real-time AI applications proliferate.

Knowledge of vector databases, embedding APIs, and LLM integration patterns (function calling, structured outputs, retry logic) differentiates AI software engineers from general software engineers. Understanding cost optimization (caching strategies, model routing, batched inference) is valuable since inference costs can dominate application economics.

Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.

Compensation Benchmarks

AI Software Engineer roles pay a median of $220,000 based on 1,601 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $229,300. This role's midpoint ($252K) sits 15% above the category median. Disclosed range: $189K to $315K.

Across all AI roles, the market median is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($256,000) and Research Engineer ($252,000). By seniority level: Entry: $111,000; Mid: $193,200; Senior: $229,300; Director: $272,300; VP: $235,830.

Rippling AI Hiring

Rippling has 12 open AI roles right now. They're hiring across AI Software Engineer, AI/ML Engineer. Positions span San Francisco, CA, US, New York, NY, US, New York, NY. Compensation range: $210K - $315K.

Location Context

AI roles in New York pay a median of $221,000 across 3,078 tracked positions. That's 4% above the national median.

Career Path

Common paths into AI Software Engineer roles include Software Engineer, Full-Stack Developer, Backend Engineer.

From here, career progression typically leads toward Staff Engineer, AI Architect, Engineering Manager.

If you're a software engineer, you're already 80% there. Learn the AI integration patterns: RAG, streaming inference, function calling, structured outputs. Build a project that demonstrates you can wrap an AI model in a production-quality application with proper error handling, caching, and user experience. That's the portfolio piece that gets you hired.

What to Expect in Interviews

Technical screens look like standard software engineering interviews with an AI twist. Expect system design questions about building reliable applications around probabilistic models: handling streaming responses, implementing retry logic for API failures, and designing caching strategies for LLM outputs. Coding rounds test standard algorithms plus practical integration patterns like async processing and rate limiting.

When evaluating opportunities: Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.

AI Hiring Overview

The AI job market has 9,079 open positions tracked in our dataset. By seniority: 106 entry-level, 4,384 mid-level, 3,343 senior, and 1,246 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (531 positions). The remaining 8,478 roles require on-site or hybrid attendance.

The market median for AI roles is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($256,000 median, 66 roles); Research Engineer ($252,000 median, 457 roles); AI Engineering Manager ($251,622 median, 55 roles).

AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.

The AI Job Market Today

The AI job market spans 9,079 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,862), AI Product Manager (453), AI Software Engineer (451). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.

The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (106) are outnumbered by mid-level (4,384) and senior (3,343) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 1,246 positions, representing the bottleneck between technical execution and organizational strategy.

Remote work availability sits at 6% of all AI roles (531 positions), with 8,478 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.

AI compensation is structured in clear tiers. The market median sits at $213,000. Top-quartile roles start at $263,911, and the 90th percentile reaches $318,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.

Category matters for compensation. AI Safety roles lead at $256,000 median, while Prompt Engineer roles sit at $141,440. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.

The most in-demand skills across all AI postings: Python (1,649 postings), Aws (898 postings), Azure (723 postings), Rag (671 postings), Gcp (536 postings), Pytorch (434 postings), Claude (410 postings), Kubernetes (406 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.

Frequently Asked Questions

Based on 1,601 roles with disclosed compensation, the median salary for AI Software Engineer positions is $220,000. Actual compensation varies by seniority, location, and company stage.
Full-stack engineering skills with AI integration experience. Python and TypeScript are the most common requirements. You'll need to understand API design, database architecture, and how to build reliable systems around probabilistic outputs. Experience with streaming, async processing, and caching patterns is increasingly important as real-time AI applications proliferate.
About 6% of the 9,079 AI roles we track offer remote work. Remote availability varies by company and seniority level, with senior and leadership roles more likely to offer location flexibility.
Rippling is among the companies actively hiring for AI and ML talent. Check our company profiles for detailed breakdowns of open roles, salary ranges, and hiring trends.
Common next steps from AI Software Engineer positions include Staff Engineer, AI Architect, Engineering Manager. Progression depends on whether you lean toward technical depth, people management, or product strategy.

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