Customer Engineer, Agent Builder

Decagon Decagon · Vertical AI · San Francisco, CA · Deployment Strategists

Customer Engineer, Agent Builder role focused on end-to-end execution of AI agent builds for enterprise customers, including configuration, integration, and validation of guardrails. Requires strong technical skills, customer interaction, and experience with LLM/AI agent development.

What you'd actually do

  1. Own end-to-end execution of AI agent builds for enterprise customers, from initial scoping through launch and iteration.
  2. Write and maintain key agent-building artifacts (e.g., AOPs), and configure agent behavior to optimize quality, reliability, and business outcomes.
  3. Configure and validate guardrails to ensure safe, compliant, and predictable agent performance across real-world scenarios.
  4. Set up, test, and validate customer integrations (e.g., ticketing systems), including building tools and workflows needed for successful deployments.
  5. Interface with senior technical stakeholders at customers to define success criteria, gather requirements, and drive delivery against timelines.

Skills

Required

  • 5+ years of relevant experience in a technical customer-facing role
  • Strong technical foundation: comfortable writing code, working with APIs, and building/validating integrations end-to-end
  • Experience delivering production-grade customer solutions that require structured execution, testing/validation, and iteration
  • Ability to communicate clearly with senior technical stakeholders, translate requirements into implementation plans, and drive delivery
  • Comfort working in fast-moving, ambiguous environments where you shape solutions as much as you implement them

Nice to have

  • Experience building with or around LLMs / AI agents (prompting, evaluation, guardrails, tooling, workflow design, etc.)
  • Experience with enterprise SaaS integrations (e.g., ticketing systems, CRM, data pipelines) and associated security/compliance considerations
  • A Computer Science, Engineering, or Math degree, or equivalent technical experience
  • Strong product instinct: ability to write crisp PRDs, define success metrics, and contribute customer insight back into product roadmap

What the JD emphasized

  • end-to-end execution
  • enterprise-quality agents
  • customer-facing
  • technical delivery
  • hands-on execution
  • structured execution
  • testing/validation
  • iteration

Other signals

  • AI agents
  • customer-facing
  • technical delivery
  • enterprise-grade performance