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 400,000 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:

Gusto is scaling our AI-powered risk function to support a complex, multi-entity business operating in highly regulated environments. As the Enterprise Risk Management Lead, you will own and operate Gusto's Enterprise Risk and Third Party Risk Management programs , built AI-first, designed to scale, and built to enable the business to move fast without breaking things.

This is a People Empowerer (manager) role. You balance hands-on program leadership with managing and developing a team of compliance professionals. You navigate the tension between "doing the work" and "leading the work" , contributing directly to complex, high-impact programs while ensuring your team delivers with excellence.

You are a change agent who influences how automated risk management gets done at Gusto, models AI-enabled ways of working, and helps others grow their own capabilities in the process.

You will champion the adoption of AI, machine learning, and process automation across risk monitoring, control testing, incident management, and reporting , and you will partner with Product, Data Science, and Engineering to make it explainable, adopted, compliant, and scalable.

Here’s what you’ll do day-to-day:

You manage initiatives that are complex in both scope and impact, influencing the strategic direction of Gusto's compliance risk management framework.

You apply a deep understanding of the regulatory landscape and how it intersects with Gusto's business model to proactively design and lead cross-functional risk programs.

You translate complex risk topics into clear, actionable guidance that senior leaders can immediately understand and operationalize.

You lead cross-functional working groups, align divergent perspectives, and drive cohesive progress toward shared goals , with minimal oversight.

As a PE, you balance individual risk and compliance contribution with team leadership.

You manage operations, professional development, resource allocation, and performance , while staying close enough to the work to be a credible, hands-on partner to your team and stakeholders.

You model responsible AI use, and act as a source of knowledge and mentorship , supporting your team's AI journey and helping others apply it responsibly and effectively.

AI-Enabled Risk Operations, Innovation & Transformation

This is how you and your team operate , not a side project.

• Champion the adoption of AI, machine learning, process automation, and advanced analytics to improve risk monitoring, control testing, and reporting across ERM, TPRM, and broader compliance functions

• Lead the integration of AI and automation into every phase of the risk lifecycle: vendor assessments, document ingestion and analysis, continuous monitoring and alerting, risk scoring, prioritization, and trend analysis

• Build intelligent risk monitoring and evaluation systems , including auto-tagging for risk issues, audit requests, and regulatory changes , that improve real-time visibility and eliminate manual effort across the enterprise risk portfolio

• Drive the digitalization of risk tools including RCSAs, KRIs, incident reporting, and audit tracking , transforming periodic, reactive processes into continuous intelligence systems with live leading and lagging indicators that enable real-time decision-making

• Partner with Product, Data Science, and Engineering to define requirements for AI-driven workflows, decisioning engines, and dashboards , ensuring explainability, auditability, and regulatory defensibility of all AI-enabled risk decisions

• Design and build intelligent dashboards and reporting tools that deliver real-time risk visibility and decision-quality insights to senior leadership and cross-functional stakeholders

• Design AI workflows with appropriate validation loops, human-in-the-loop checkpoints, and guardrails , ensuring outputs are reliable, governable, and meet regulatory standards before being used to frame risks, recommendations, or decisions

• Stay current on AI advancements and emerging technologies and proactively integrate new capabilities into team operations to increase velocity and scale

• Model responsible AI use , supporting ICs in their AI journeys and fostering a culture of intentional experimentation, accountability, and continuous improvement

Enterprise Risk Management

• Design, implement, and continuously improve Gusto's ERM framework, ensuring alignment with best practices and Gusto's stage of growth and strategic priorities across all entities

• Define and maintain Gusto's enterprise risk taxonomy, risk appetite statement, and key risk indicators spanning operational, regulatory, technology, financial, and reputational risk domains

• Lead Gusto's Enterprise Risk Management process , driving integration of risk practices across business functions, promoting a proactive risk culture, and ensuring incident management, root cause analysis, and lessons learned are systematically captured in an automated, AI forward way.

• Apply AI-assisted insights to enterprise risk datasets to surface systemic patterns, validate assumptions, prioritize risks, and deliver proactive, data-driven advisory to senior leadership

• Monitor the regulatory landscape (OCC, FDIC, CFPB, SEC, FINRA, GDPR, NIST, ISO, SOC) and leverage AI to proactively incorporate changes before they become compliance gaps

• Act as a key advisor to senior compliance leadership , translating complex risk findings into clear, actionable recommendations with minimal oversight

Third Party Risk Management (TPRM)

• Design, implement, and independently manage a high-impact, AI-first TPRM program with clear milestones, progress tracking, and measurable outcomes across all Gusto entities

• Manage the full third-party risk lifecycle , onboarding and risk profiling, periodic assessments, issue management, corrective action tracking, and offboarding , across suppliers, product partners, contractors, service providers, and cloud service providers , and do so in an AI and automated way.

• Maintain a centralized, authoritative vendor risk inventory and risk register, ensuring real-time visibility into Gusto's third-party risk posture

• Conduct periodic AI-driven audits and reviews of third-party compliance with contractual obligations and regulatory standards, identifying patterns that inform continuous program improvement

• Serve as the central orchestrator across Compliance, Security, Legal, Procurement, IT, and GRC for proactive and reactive third-party incident management

• Own Gusto's TPRM policy and maintain comprehensive documentation , risk assessments, audit findings, corrective actions , ensuring full accountability and traceability

People Leadership & Team Development

• Balance individual compliance contribution with team leadership , managing operations, professional development, resource allocation, and performance while staying close to the work

• Coach and develop ICs toward next

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LLM & AI Pipeline Engineering - Design, build, and maintain production-grade LLM integration pipelines , including retrieval-augmented generation (RAG), prompt engineering, output parsing, and chain orchestration.

Develop and operate AI features within Jeeves's core financial products: spend categorization, document extraction, anomaly detection, financial Q&A, and automated reconciliation.

Implement structured output validation, fallback handling, and confidence scoring to ensure AI decisions meet reliability standards for financial use cases.

Evaluate and integrate AI frameworks and tools (LangChain, LlamaIndex, OpenAI API, Anthropic API, HuggingFace, vector databases) and advocate for the right tool for the job.

Establish prompt versioning and evaluation practices to ensure AI outputs remain accurate and consistent as models and data evolve.

Retrieval & Vector Search - Design and maintain vector search pipelines using databases such as Pinecone, Weaviate, or pgvector to power semantic search and RAG-based features.

Build document ingestion and chunking pipelines for Jeeves's financial data , processing invoices, receipts, policy documents, and transaction records.

Optimize retrieval quality through embedding model selection, chunk strategy, metadata filtering, and re-ranking techniques.

ML Model Serving & Operations - Collaborate with data scientists to take trained ML models from experimental notebooks to production serving infrastructure.

Build and maintain model serving endpoints with appropriate latency SLOs, input validation, and output monitoring.

Implement model performance monitoring and data drift detection to ensure production models remain accurate over time.

Support model retraining workflows by designing clean data pipelines and feature engineering that can be continuously updated.

Backend Integration & Reliability - Integrate AI services cleanly with Jeeves's backend microservices , designing clear API contracts, circuit breakers, and graceful degradation patterns.

Write high-quality, testable backend code in Python or Go/Node.js to power AI-integrated features.

Instrument AI components with structured logging, distributed tracing, latency dashboards, and alerting to ensure operational visibility.

Collaboration & Growth - Partner with Product, Backend Engineering, and Data Science to define the AI roadmap and translate requirements into reliable systems.

Contribute to a culture of quality by writing design docs, reviewing peers' AI system designs, and sharing learnings openly.

Help grow the AI engineering practice at Jeeves by establishing patterns, tooling, and best practices that the broader team can build on.

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