Staff Software Engineer, AI Developer Tools

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.

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.

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.

• →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.

• 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.