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Solutions Engineer

  • Toronto, ON, Canada

Full-time

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Job details

Job type
Full-time
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Posting language
English
Posted

Original job description

About Us:

Mosaic AI is the only enterprise AI platform built for technical support in highly configurable, multi-product companies. We unify the customer, product, and support context scattered across a company's systems, then act on it across the case lifecycle: automating what we can, escalating to a human expert when it matters. Built on 100+ deep integrations, the platform runs products already live in production, including Self-Service, Knowledge, Triage, Assist, Intelligence, Alerting, and QA, all sharing one foundation so they ship fast and improve as the platform grows.

That shared foundation makes this an exciting, unusual place to build. Each product we launch would have been an entire company in the pre-AI era; for us, it's a focused product on common infrastructure, so each deployment builds on the last. Our no-code Agent Builder lets teams design and deploy agents with governance and traceability, while our Customer Context Model routes recurring issues and account risk to the teams that can fix them. Every deployment lowers our customers' cost to serve. We're hiring engineers and product leaders who want to build systems that get more capable the more they run.

About The Role

We’re hiring a Solutions Engineer to own the technical and operational success of our customers from pre-sale through post-sale. This is a full-lifecycle role: you’ll run POVs, lead onboarding, configure and tune AI workflows, and drive real adoption and expansion outcomes.

This is not a demo jockey role. You will be embedded with customers to make AI work in production - configuring integrations, managing agent performance, solving real workflow problems, and proving value.

Requirements:

What You’ll Do:

  • Partner with AEs to run high-impact POVs (proof-of-value pilots)
  • Own technical validation: data mapping, light integrations, prompt setup, outcome measurement
  • Be the technical face of the company in pre-sale cycles
  • Own onboarding: configure AI workflows, connect integrations, ensure functional go-live
  • Drive activation: monitor AI output quality, guide user enablement, tune prompts and logic
  • Prove and communicate value: track impact metrics, partner with AE and Value team on expansions
  • Retain ownership of technical success through renewals

Who You Are:

  • AI-fluent: You understand how AI models work (prompting, edge cases, accuracy, drift) and can speak confidently about them with customers.You stay ahead of AI trends, experiment with the latest tools and techniques, and aren't afraid to hack together fast, creative solutions to demonstrate what’s possible. You know that delivering AI in the wild takes iteration, curiosity, and a builder’s mindset.
  • Technical: You’re comfortable reading API docs, debugging JSON payloads, writing basic SQL, and working hands-on with data.
  • Operational: You can map a customer’s workflow, translate it into a system configuration, and drive the changes needed to make AI stick.
  • Customer-facing: You can lead a technical working session and hold the room in an executive QBR.
  • Outcome-oriented: You don’t just deliver tasks - you deliver successful, referenceable deployments that grow.

Experience We’re Looking For:

  • 2–4 years in a solutions engineering, technical consulting, TAM, or implementation role at a SaaS, AI, automation, or consulting firm
  • Experience working directly with AI powered products, workflow automation platforms, and GTM systems (e.g., Salesforce, Zendesk, Intercom, Atlassian, Gong)
  • Strong working knowledge of API integrations - including how to read API docs, test endpoints, structure payloads, and debug authentication or schema issues
  • Familiarity with SaaS delivery models, including onboarding, post-sale deployment, and customer success workflows
  • Ability to independently manage technical customer projects end-to-end - from pre-sale pilots to full production delivery and ongoing optimization

Why This Role Matters:

We’re an AI-native platform used by GTM and CX teams in modern B2B SaaS companies. Our customers trust us to leverage AI to transform how their customer facing teams operate. This role is the tip of the spear in making that real. You’re the difference between a cool demo and a live deployment that drives revenue.
More about this job

Responsibilities

Lead customer technical success throughout the full lifecycle, from pre-sale proof-of-value pilots and technical validation through onboarding, production deployment, optimization, and renewals. Configure integrations and AI workflows, monitor and improve agent performance, enable users, and demonstrate customer value to support adoption and expansion.

Requirements

The role seeks 2–4 years of experience in solutions engineering, technical consulting, technical account management, or implementation, ideally with AI-powered products, workflow automation, and go-to-market systems. Candidates should be comfortable with API documentation and integrations, JSON payloads, basic SQL, customer workflow configuration, and independently managing technical projects from pilot to production.

Skills

  • Solutions Engineering
  • AI Workflow Configuration
  • Prompt Engineering
  • API Integrations
  • Data Mapping
  • JSON Debugging
  • SQL
  • Workflow Automation
  • Customer Onboarding
  • Technical Validation
  • AI Performance Monitoring
  • Customer Enablement
  • Project Management
  • Value Measurement
  • Executive Communication

Visa sponsorship

Not detected in the job text

Categories

  • Technology
  • Software
  • Customer Service & Support
  • Sales
  • Consulting

Keywords

  • Artificial Intelligence
  • AI Agents
  • Agent Builder
  • Prompt Engineering
  • AI Workflow Automation
  • API Integrations
  • API Documentation
  • JSON
  • SQL
  • Data Mapping
  • Technical Validation
  • Proof Of Value
  • Customer Onboarding
  • SaaS
  • Salesforce
  • Zendesk
  • Intercom
  • Atlassian
  • Gong
  • Customer Success
  • Go-To-Market Systems
  • Workflow Configuration
  • AI Performance Monitoring
  • Outcome Measurement
  • Customer Experience
  • Technical Consulting
  • Production Deployment
  • Renewals
  • Expansion
  • Customer Context Model

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