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Added 1 min ago
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Urban Ridge Supplies

Agent Deployment Engineer

Toronto, ON, Canada

Job type: Full-time
Posting language: English
Posted: Sep 24, 2026

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Original job description

About Decagon

Decagon is the leading conversational AI platform empowering every brand to deliver concierge customer experiences.

Our technology enables industry-defining enterprises like Avis Budget Group, Block’s Cash App and Square, Chime, Oura Health, and Hunter Douglas to deploy AI agents that power personalized, deeply satisfying interactions across voice, chat, email, SMS, and every other channel.

We’re building a future where customer experiences are being redefined from support tickets and hold music to faster resolutions, richer conversations, and deeper relationships. We’re proud to be backed by world-class investors who share that vision, including a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures, along with many others.

We’re an in-office company, driven by a shared commitment to excellence and velocity. Our values - Just Get It Done, Invent What Customers Want, Winner’s Mindset, and The Polymath Principle - shape how we work and grow as a team.

About The Team

Over the past few years, development of LLMs has evolved at a rapid pace. It’s not enough for our customers to just “set it and forget it” when it comes to AI software. Truly successful AI Agents require hands-on execution, rigorous iteration, and deep technical delivery to reach enterprise-grade performance.

We’re creating an Agent Deployment Engineering Org : a specialized technical delivery team responsible for end-to-end execution of AI agent builds. Agent Deployment Engineers own the hands-on work required to deliver best-in-class agents - writing and configuring key components, validating integrations, and ensuring agents perform reliably at scale. This team brings greater specialization and focus to build quality. Agent Deployment Engineers are technical and customer-facing: you’ll interface with senior technical stakeholders on the customer side while also going deep on agent configuration and build execution.

About The Role

As an Agent Deployment Engineer, you will be responsible for end-to-end execution of AI agent builds for strategic customers. This is a highly technical delivery role where you will own the implementation work required to launch and scale enterprise-quality agents - partnering with customers and internal teams to define success, translate requirements into build plans, and deliver agents that meaningfully impact the customer’s business.

You’ll work closely with Agent PMs, Agent Success, Engineering, and GTM teams to create tight feedback loops: executing builds, surfacing gaps, and influencing the evolution of Decagon’s agent-building platform based on real customer needs. This role is ideal for someone who thrives in fast-moving environments, enjoys shipping customer-facing technical work, and can balance hands-on execution with structured thinking.

In this role, you will

Own end-to-end architecture and execution of AI agent builds for enterprise customers, from systems design and initial scoping through implementation, evaluation, and production deployment.
Design and engineer the core agentic logic governing agent behavior, applying engineering principles to optimize quality, reliability, and correctness across non-deterministic model outputs.
Engineer and validate layered guardrails and supervisory controls to ensure safe, compliant, and predictable agent performance across real-world scenarios.
Architect, build, and test integrations with customer systems (e.g., data pipelines, CRMs, ticketing systems), including building the tools, APIs, and workflows needed for reliable deployments at scale.
Interface with senior technical stakeholders at customers to define success criteria and system requirements, and drive technical delivery against timelines.
Diagnose, debug, and resolve both probabilistic and technical failures through root-cause analysis of execution traces, error logs, and model behavior.
Design evaluation and regression-testing frameworks to validate agent behavior against ground truth and guard against performance drift.
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.

Benefits

We proudly offer the following benefits for our full-time employees:

Medical, Dental, and Vision benefits for you and your family
Life Insurance and Disability Benefits
Retirement Plan (e.g., 401K, pension)
Parental Leave
Fertility and family building benefits through Carrot
Monthly stipend to support your wellness, lifestyle, and work-life balance
Daily lunches and snacks in the office to keep you at your best
Take what you need vacation policy (subject to local requirements; UK employees receive 25 days of statutory leave)

These benefits are described in more detail in Decagon’s policies, may vary by location, and can change at any time according to applicable compensation and benefits plans.

Job Id: QfQbHLqZwsBBmDCzpSy/E7Iivscap/X7wGHka2HxTYeEWyO7koFai2mCIL2pYZVeCH0k48m/QmCYgt31DEdnRTrwyuqeqL59vQ==

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More about this job

Responsibilities

You will own the end-to-end architecture and execution of AI agent builds for enterprise customers, from initial scoping to production deployment. You will also design agentic logic, build system integrations, and collaborate with internal teams to drive platform improvements based on customer feedback.

Requirements

The role requires 5+ years of experience in a technical customer-facing role with a strong foundation in coding and API integration. Candidates should have experience delivering production-grade solutions and the ability to communicate effectively with senior technical stakeholders.

Skills

AI agent deployment
LLM development
Systems design
API integration
Technical delivery
Customer-facing
Software engineering
Debugging
Root-cause analysis
Data pipelines
CRM integration
Guardrails design
Evaluation frameworks
Technical documentation
Requirement scoping
Product roadmap contribution

Benefits

Medical benefits
Dental benefits
Vision benefits
Life insurance
Disability benefits
Retirement plan
Parental leave
Fertility and family building benefits
Wellness stipend
Daily lunches and snacks
Vacation policy

Visa sponsorship

Not detected in the job text

Keywords

Conversational AI
LLM
AI Agents
SaaS
Systems Design
API
CRM
Data Pipelines
Ticketing Systems
Deployment
Engineering
Solutions Engineering
Technical Consulting
Implementation Engineering
Product Management
Guardrails
Regression Testing
Root-cause Analysis
Enterprise Software
Architecture
Automation
Workflow Design
Compliance
Security
PRD
Customer Success
Go-To-Market
Technical Delivery
Model Evaluation
Software Development

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