Build and scale Otto, Gusto’s production AI agent for support advocates, spanning the LLM runtime, tool/action layer, backend, frontend, and evaluation systems. The role requires 8+ years of software engineering experience, production agentic-system expertise, strong full-stack ability, and mentoring skills.
Salary not listed
Hybrid8+ YOEFullstack Engineering
About the role
Responsibilities
Design and build across the Otto platform, including the runtime and agent graph, tool/action layer, Rails/GraphQL backend, advocate-facing experience, and evaluation system.
Expand the agent's safe capabilities through autonomous, tool-using actions with human-in-the-loop approval.
Build secure, auditable identity and permissions models for agent actions.
Develop evaluation and observability systems using LLM-as-judge, deterministic scorers, offline gates, and online production monitoring.
Work with LLMs on prompting, tool/function design, retrieval, and feedback loops based on advocate interactions.
Partner with Product, Data, Design, and Customer Experience teams to ship capabilities addressing advocate and customer pain points.
Mentor engineers and establish responsible practices for building agentic systems at scale.
Requirements
Typically 8+ years of software engineering experience with end-to-end system ownership.
Production experience building and shipping LLM-powered or agentic systems, including tool-calling, retrieval, or evaluations.
Strong full-stack range across backend services, LLM runtimes, and customer-facing products.
Experience owning multi-quarter projects with measurable user impact at scale.
Sound judgment regarding safety and blast radius when software takes actions on real accounts.
Ability to mentor engineers and raise engineering standards.
Nice to Have
Experience with agent frameworks, evaluations, LLM-as-judge, retrieval, or MCP-style tool architectures.
Experience with Ruby on Rails and/or JavaScript/React, or ability to ramp quickly.
Familiarity with GraphQL and federated backends.
Appreciation for collaborative, test-driven, high-autonomy environments and clear communication with engineering and business stakeholders.
Compensation and Benefits
Competitive base pay, benefits, and equity in the form of RSUs.
Offer amounts are determined by role, level, and location.
Skills
llm agentsagent runtimetool callingretrievalllm evaluationRuby on RailsJavaScriptReactGraphQLfederated backendsmcpPrompt EngineeringObservabilityrails
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