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DecagonDecagon

Customer Engineer, Agent Builder

Owns end-to-end execution of AI agent builds for enterprise customers, configuring agents, validating integrations, and collaborating with stakeholders to deliver scalable solutions. Requires 5+ years in technical customer-facing roles with strong coding and API skills.

About the job

In this role, you will

  • 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.

Your background looks something like this

  • Have 5+ years of relevant experience in a technical customer-facing role (e.g., 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.
  • 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.

Even better if you 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.

Compensation

$175K – $230K • Offers Equity

Skills

LLMs, AI Agents, APIs, Prompting, Guardrails, Integrations, Ticketing Systems, CRM, SaaS, Code

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