Decagon — Customer Engineer, Agent Builder (TO

Decagon — Customer Engineer, Agent Builder (TO)

Type: Full-time | On-site | Toronto, Canada
Compensation: $150,000–$200,000 + Competitive Equity
Hiring count: 2
Visa sponsorship: H-1B (per Contrario structured field — see note; role is Toronto-based)
Reports to: TBD

Decagon is the leading conversational AI platform helping brands deliver concierge-level customer experiences. Enterprises including Avis Budget Group, Cash App and Square (Block), Chime, Oura, and Hunter Douglas run Decagon's AI agents across voice, chat, email, SMS, and other channels. Backed by a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures.

The Agent Builder org was stood up in Q1 and currently has 7–8 people, working one-to-one with some of Decagon's largest strategic customers (Hertz, Delta, and Amex among them). As the team scales, agent builders will support more customers concurrently. Decagon is an in-office company built around velocity and hands-on execution.

Founded: 2023 | Team size: 201–500 | Stage:
Series D+Industry: Consumer Tech / Conversational AIWebsite: decagon.ai Office:
Toronto, Canada

• Category leader with elite backing: Leading conversational AI platform, live at scale with marquee enterprises (Avis, Cash App, Chime, Oura), backed by a16z, Accel, BCV, Coatue, and Index.
• High-ownership, end-to-end seat: Own agent builds from scoping through launch and iteration; write and configure core components and interface directly with senior technical stakeholders on the customer side.
• Early on a scaling org: Agent Builder team is ~7–8 people, stood up in Q1, working one-to-one with Decagon's largest strategic accounts — early enough to shape how the function scales.

• An intake video is on the Contrario page but was not transcribed in the pasted HTML, so no written intake summary is available yet. Share the transcript or notes to populate this section.

Own end-to-end execution of AI agent builds for enterprise customers — from scoping through launch and iteration. A highly technical delivery seat: write and configure core components, validate integrations, and interface directly with senior technical stakeholders on the customer side. The build/customer split is dynamic, generally landing near 50/50 to 60/40 technical-to-customer-facing.

• End-to-end execution of AI agent builds for enterprise customers, from scoping through launch and iteration
• Write and maintain key agent-building artifacts; configure agent behavior for quality, reliability, and business outcomes
• Configure and validate guardrails for safe, compliant, predictable agent performance
• Set up, test, and validate customer integrations (ticketing systems and comparable), building any tools or workflows needed
• Interface directly with senior technical stakeholders to define success criteria and drive delivery against timelines
• Partner closely with Agent PMs, Engineering, Design, and GTM to deliver consistent, repeatable agent builds

Tech stack: Python (hard requirement); REST APIs and enterprise integrations; LLM / AI-agent tooling (prompting, evaluation, guardrails, workflow design)

• 5–7 years of experience in a technical customer-facing role (solutions engineering, forward-deployed engineering, technical consulting, implementation engineering, technical PM, or comparable)
• Strong Python proficiency (hard requirement)
• API integration experience end to end — comfortable writing code, working with APIs, and building or validating integrations
• Experience delivering production-grade customer solutions requiring structured execution, testing, and iteration
• Clear communicator who can translate requirements into implementation plans and drive delivery with senior technical stakeholders

Nice-to-have: experience building with or around LLMs and AI agents (prompting, evaluation, guardrails, tooling, workflow design); enterprise SaaS integrations (ticketing, CRM, data pipelines) with associated security/compliance exposure;
Computer Science, Engineering, or Math degree or equivalent; strong product instinct (crisp requirements docs, success metrics).

• Software engineering…