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About This Role
About Gusto
At Gusto, we're on a mission to grow the small business economy. We handle the hard stuff — payroll, health insurance, 401(k)s, and HR — so owners can focus on their craft and their customers. With teams in Denver, San Francisco, and New York, we support more than 500,000 small businesses nationwide and are building a workplace that reflects the people we serve.
All full\-time employees receive competitive base pay, benefits, and equity (RSUs) — because everyone who helps build Gusto should share in its success. Offer amounts are determined by role, level, and location. Learn more about our Total Rewards philosophy.
AI is a fundamental part of how work gets done at Gusto. We expect all team members to actively engage with AI tools relevant to their role and grow their fluency as the technology evolves. AI experience requirements vary by role and will be assessed during the interview process.
About the Role:
As a Staff Engineer on the Developer Productivity \- AI Developer Tools team, you will be the architectural anchor shaping the AI platform that accelerates engineering across Gusto. You will redefine how our entire engineering organization builds, tests, and ships software by architecting a highly secure, context\-aware, "AI\-native" development lifecycle.
Your mission is to eliminate developer friction through AI tools, multi\-agent systems, and intelligent automation. Whether you are building bespoke internal coding assistants, automating sprawling codebase refactors, or deploying AI to self\-heal CI/CD pipelines, your work will directly multiply the velocity of hundreds of builders. Help us drive developer productivity by building the next generation of AI tools.
About the Team:
The AI Developer Tools team is a specialized team within Developer Productivity. We believe AI is the next great leap in software craftsmanship. Our goal is to provide every builder at Gusto with a suite of "superpowers" tools that deeply understand our codebase and absorb operational toil so engineers can focus on creative problem\-solving. We treat our fellow engineers as our primary customers, prioritizing developer experiences that are not just powerful, but absolutely delightful to use.
Here’s what you’ll do day\-to\-day:
- Architect AI Core Infrastructure: Design, scale, and maintain the internal platform and APIs that integrate LLMs into the developer workflow, with a heavy focus on autonomous agents, custom retrieval\-augmented generation (RAG), and smart context\-delivery systems.
- Drive Technical Leadership \& Vision: Establish engineering best practices for building with AI at Gusto, including robust evaluation frameworks (evals), guardrails for code safety, and strategies for optimizing model latency and token spend.
- Collaborate \& Evangelize: Partner closely with product engineering teams to uncover systemic friction points, and collaborate with core Infrastructure and Security teams to ensure all AI tooling is scalable, compliant, and secure.
- Optimize Feedback Loops: Identify and eliminate critical bottlenecks in the local\-to\-production lifecycle at scale across Gusto.
- Maintain Enterprise Reliability: Treat AI infrastructure with production\-grade rigor. Monitor system health, diagnose complex integration or networking issues, and mitigate model drift or downtime.
Here’s what we're looking for:
- 8\+ Years of Systems Expertise: You are a seasoned engineer who is highly comfortable navigating massive, complex codebases and delivering production\-grade, distributed software.
- Production AI Experience: You have a proven track record of moving AI beyond prototypes. You possess a deep understanding of prompt engineering, fine\-tuning, RAG architectures, and orchestrating multi\-agent workflows.
- Developer\-First Mindset: You are passionate about Developer Experience and Productivity. You intuitively understand what makes an internal tool frictionless, fast, and empowering for other engineers.
- Strategic Execution: You don't just build wrappers; you think deeply about data privacy, security, cost management, and systemic reliability when deploying AI solutions.
- Exceptional Communication: You can seamlessly translate bleeding\-edge AI capabilities into clear, actionable infrastructure strategies, mentoring junior engineers and aligning cross\-functional stakeholders along the way.
- Working as a Team: You work across team boundaries and bring other teams and groups along with you towards our strategic vision.
Our cash compensation amount for this role is targeted at $180,000/yr to $200,000/yr in Denver \& most remote locations, $220,000/yr to $245,000/yr for San Francisco, New York \& Seattle. Stock equity is additional. Final offer amounts are determined by multiple factors including candidate experience and expertise and may vary from the amounts listed above.
Gusto has physical office spaces in Denver, San Francisco, and New York City. Employees who are based in those locations will be expected to work from the office on designated days approximately 2\-3 days per week (or more depending on role). The same office expectations apply to all Symmetry roles, Gusto's subsidiary, whose physical office is in Scottsdale.
Note: The San Francisco office expectations encompass both the San Francisco and San Jose metro areas.
When approved to work from a location other than a Gusto office, a secure, reliable, and consistent internet connection is required. This includes non\-office days for hybrid employees.
Our customers come from all walks of life and so do we. We hire great people from a wide variety of backgrounds, not just because it's the right thing to do, but because it makes our company stronger. If you share our values and our enthusiasm for small businesses, you will find a home at Gusto.
Gusto is proud to be an equal opportunity employer. We do not discriminate in hiring or any employment decision based on race, color, religion, national origin, age, sex (including pregnancy, childbirth, or related medical conditions), marital status, ancestry, physical or mental disability, genetic information, veteran status, gender identity or expression, sexual orientation, or other applicable legally protected characteristic. Gusto considers qualified applicants with criminal histories, consistent with applicable federal, state and local law. Gusto is also committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. We want to see our candidates perform to the best of their ability. If you require a medical or religious accommodation at any time throughout your candidate journey, please fill out this form and a member of our team will get in touch with you.
Gusto takes security and protection of your personal information very seriously. Please review our Fraudulent Activity Disclaimer.
Personal information collected and processed as part of your Gusto application will be subject to Gusto's Applicant Privacy Notice.
Salary Context
This $180K-$245K range is above the median for AI Software Engineer roles in our dataset (median: $190K across 219 roles with salary data).
Role Details
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 3,823 AI roles we're tracking, AI Software Engineer positions make up 7% of the market. At Gusto, 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
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 $232,000 based on 797 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($212K) sits 8% below the category median. Disclosed range: $180K to $245K.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.
Gusto AI Hiring
Gusto has 1 open AI role right now. They're hiring across AI Software Engineer. Based in Denver, CO, US. Compensation range: $245K - $245K.
Location Context
AI roles in Denver pay a median of $184,000 across 159 tracked positions. That's 8% below 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 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 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 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). 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 (112) are outnumbered by mid-level (1,798) and senior (1,516) 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 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 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 $200,100. Top-quartile roles start at $253,500, and the 90th percentile reaches $307,500. 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 Engineering Manager roles lead at $275,000 median, while Prompt Engineer roles sit at $140,000. 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 (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 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
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