Agentic Operations Architect Denver, CO - Hybrid; Las Vegas, NV - Remote Phoenix

Denver, CO
- Hybrid;
Las Vegas, NV
- Remote;
New York, New York, United States;
Phoenix, AZ
- Remote;
San Francisco, CA
- Hybrid

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  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 an Agentic Operations Architect, you will own the reusable capabilities that make agentic service workflows possible, the patterns, primitives, standards, and tooling that other builders across the org use to automate discrete customer problems. You are not the owner of any single workflow. You are the reason a workflow that took six weeks takes two, and the reason the tenth one is safer than the first.

You will prototype workflows yourself, but as a means to an end: to prove a pattern is sound, to find out what builders are missing, and to earn the right to set a standard.

About the Team:

The mission of our Service Transformation (CXT) team is to quickly evolve and scale how Gusto delivers outstanding service experiences and leverages AI to do so. Our team designs the systems, governance frameworks, and feedback loops that allow Gusto's service model to improve continuously, operate reliably, and earn the trust of the customers and employees who depend on it.

Here’s what you’ll do day-to-day:

Build the patterns

• Design the reusable patterns for agentic service workflows, orchestration, HITL protocols, override and escalation logic, quality safeguards, so builders assemble from proven components
• Set the standards builders work to, concrete enough to apply without you in the room
• Prototype workflows selectively: to validate a pattern, expose a gap, or unblock a hard problem, then extract the reusable part and hand it off
• Pull learnings from every build back into the shared patterns, so each one is faster and safer than the last

Shape the platform

• Influence Product on what to build next: turn what's slowing builders down into specific, prioritized asks backed by evidence
• Prototype around gaps the platform doesn't cover yet, proving a capability is worth building before USP invests
• Be honest in both directions about the distance between what builders need and what exists

Point capacity at the right problems

• Rank automation opportunities by volume, risk, and customer impact, mining SOPs, operational metrics, and interaction data, to determine what gets built and where builders go
• Work with Data to define how workflow performance gets measured, so every builder measures the same way
• Identify where there are processes which exist which should not be automated

Carry the quality stakes

• Bring what's at stake for customers into Legal, Security, Compliance, and platform reviews, so requirements land in the patterns instead of getting retrofitted per workflow
• Represent how the portfolio is performing to senior stakeholders, briefly, and in a way that drives action

Here’s what we're looking for:

• 8+ years in operations, product, or AI roles — with at least 2 years designing and deploying AI-assisted or agentic workflows in production
• Hands‑on experience with agentic tooling, orchestration frameworks, or MCP‑style integrations, including multi‑agent coordination — conceptual familiarity is not sufficient at this level
• Strong fluency with LLM systems: prompt design, evaluation, and how models actually behave at scale
• Experience designing human‑in‑the‑loop systems with clear escalation logic, override…