Customer Engineer, Agent Builder

Decagon’s Agent Builder Org is a specialized technical delivery team that executes end-to-end AI agent builds for enterprise customers. As a Customer Engineer, Agent Builder, you’ll own the implementation work from scoping to launch, partnering with customers and internal teams to deliver enterprise-grade agents that drive meaningful business outcomes.

What youll do

• Own end-to-end execution of AI agent builds for enterprise customers, from initial scoping through launch and iteration.
• Write and maintain key agent-building artifacts (e.g., AOPs), and configure agent behavior to optimize quality, reliability, and business outcomes.
• Configure and validate guardrails to ensure safe, compliant, and predictable agent performance across real-world scenarios.
• Set up, test, and validate customer integrations (e.g., ticketing systems), including building tools and workflows needed for successful deployments.
• Interface with senior technical stakeholders at customers to define success criteria, gather requirements, and drive delivery against timelines.
• Translate customer needs into clear internal documentation and run tight feedback loops with Engineering to drive platform improvements.
• Partner closely with APMs, Engineering, Design, and Go-To-Market teams to deliver consistent, repeatable, best-in-class agent builds.

What Decagon is looking for

• 5+ years of relevant experience in a technical customer-facing role (solutions engineering, forward-deployed engineering, technical consulting, implementation engineering, technical product/PM, or similar).
• Strong technical foundation: comfortable writing code, working with APIs, and building/validating integrations end-to-end.
• Proven ability to deliver production-grade customer solutions requiring structured execution, testing, validation, and iteration.
• Excellent at communicating with senior technical stakeholders, translating requirements into implementation plans, and driving delivery.
• Comfortable working in fast-moving, ambiguous environments where you shape solutions as you implement them.
• Experience building with or around LLMs / AI agents (prompting, evaluation, guardrails, tooling, workflow design).
• Experience with enterprise SaaS integrations (ticketing systems, CRM, data pipelines) and security/compliance considerations.
• Proficiency in Python and experience working with APIs and building integrations.
• Experience configuring and validating guardrails for safe, compliant agent performance.
• Willingness to work 5 days a week in-office in San Francisco.
• Commitment to completing a 3-day take-home case study.
• Strong CS fundamentals or equivalent technical experience.