Head of AI and Machine Learning Engineering

About the role

You will lead, manage, and develop a broad AI and Machine Learning Engineering organization at Gusto, spanning Machine Learning Engineering, ML Platform, Risk Data Science, and AI Scientists, fostering a culture of technical excellence, customer impact, collaboration, and continuous learning. You will define and execute Gusto's AI and ML systems strategy, unifying classical machine learning, generative AI, risk modeling, and platform capabilities into a coherent approach that supports Gusto's broader business and product goals. You will partner with senior leaders across product, engineering, design, data, risk, legal, security, and business teams to identify where AI and ML can create meaningful customer value, business impact, and operational leverage. You will shape how AI-native products and internal systems are built at Gusto, helping teams translate business problems into end-to-end AI and ML systems with clear standards for evaluation, monitoring, observability, reliability, safety, governance, and long-term maintainability. You will lead the development and maturation of AI and ML platform capabilities, tooling, primitives, guardrails, and deployment patterns that make it easier for product and engineering teams to build, evaluate, deploy, and operate AI and ML systems with less friction, more autonomy, and the right quality bar. You will drive disciplined technical and business judgment around AI and ML investments, including where to build, where to leverage existing capabilities, and where to avoid unnecessary complexity. You will establish clear operating models, quality bars, and feedback loops so that AI and ML systems are reliable, measurable, and aligned with customer needs over time. In this role, you are expected to actively engage with AI tools relevant to your function and grow your fluency as the technology evolves.

Key facts

What you'll do

Lead, manage, and develop a broad organization spanning Machine Learning Engineering, ML Platform, Risk Data Science, and AI Scientists, fostering a culture of technical excellence, customer impact, collaboration, and continuous learning.

Define and execute Gusto's AI and ML systems strategy, unifying classical ML, GenAI, risk modeling, and platform capabilities into a coherent approach aligned with business and product goals.

Partner with senior leaders across product, engineering, design, data, risk, legal, security, and business teams to identify where AI and ML can create meaningful customer value, business impact, and operational leverage.

Shape how AI-native products and internal systems are built at Gusto, translating business problems into end-to-end AI and ML systems with standards for evaluation, monitoring, observability, reliability, safety, governance, and long-term maintainability.

Lead the development and maturation of AI and ML platform capabilities, tooling, primitives, guardrails, and deployment patterns to reduce friction and enable autonomy while maintaining quality.

Drive disciplined technical and business judgment around AI and ML investments, including decisions on where to build, where to leverage existing capabilities, and where to avoid unnecessary complexity.

Establish clear operating models, quality bars, and feedback loops so that AI and ML systems are reliable, measurable, and aligned with customer needs over time.

Act as a senior technical executive who combines deep engineering credibility, strong business judgment, and executive-level influence to make AI a durable advantage for Gusto.

Set direction for how Gusto builds, deploys, evaluates, and scales AI and ML systems across the company, ensuring alignment with product strategy and operational realities.

Champion a product-minded approach to AI and ML, balancing innovation with pragmatic delivery and clear business outcomes.

Promote cross-functional collaboration to ensure AI and ML initiatives are feasible, secure, compliant, and aligned with risk and legal standards.

Own the end-to-end lifecycle of AI and ML systems, from experimentation and prototyping through evaluation, deployment, monitoring, feedback loops, and governance.

Champion measurement and data-driven decision-making, establishing observability and feedback mechanisms to guide continuous improvement.

Mentor and grow teams by setting expectations, providing guidance, and creating an environment where technical rigor and learning thrive.

Requirements

You have deep experience in building and leading high-performing technical organizations, with a track record of managing and developing teams in machine learning, ML platform, and data science environments.

You have strong expertise in classical machine learning and emerging generative AI approaches, and you understand how to unify them into a coherent technical strategy.

You have extensive experience working with rich product and customer data to build AI and ML-powered systems that improve customer experiences and automate complex workflows.

You have a strong background in risk modeling and data science as it applies to financial services or regulated environments.

You are comfortable operating at the intersection of product, engineering, data, and policy, and you can navigate complex stakeholder environments to drive alignment.

You have a history of making sound technical and business tradeoffs, balancing speed, quality, reliability, and long-term maintainability.

You are fluent in AI and ML platform patterns, including tooling for deployment, monitoring, observability, and guardrails.

You are comfortable with ambiguity and can lead through influence, clear communication, and consistent decision-making in a fast-paced environment.

You are based in one of our office locations in Denver, San Francisco, or New York and are able to work onsite with your team.

Nice to have

Experience scaling AI and ML platforms in production environments with high reliability and security standards.

Background working with small business payroll, tax, or HR data and workflows.

Experience establishing operating models, governance frameworks, and quality standards for AI and ML within product organizations.

Practical notes

This is a full-time role based in one of our office locations in Denver, CO; San Francisco, CA, or New York, NY. Travel may be required between offices.

Employment is at-will. All offers are contingent on successful completion of background checks.