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AI Solutions Engineer

AI Summary
Superside is seeking a client-facing AI Solutions Engineer to partner with Account Executives and Account Managers before deals close. The role leads discovery, designs technically feasible AI and creative-service solutions, scopes and prices systems engagements, and develops customer proposals. It bridges sales, engineering, product, studio, and deployment teams, remaining involved with major enterprise accounts after handoff. Success requires consultative selling, practical experience building agentic workflows, solution architecture skills, and strong written and verbal English communication.
Remote from
Canada
Salary
Undisclosed
Department
Sales
Employment
Full Time
Experience
Open level
Published
Apply before
4 Dec 2026
Listing views
22
Application actions
2
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Opportunity details

About this role.

Superside is hiring an AI Solutions Engineer to be the technical partner to our Account Executives and Account Managers before a deal closes. You’ll find out what a client really needs, work out what is technically possible, and design the solution that delivers it, whether the answer is using our creative services team, an AI system, or both.

You start from the customer’s problem, not the product. You understand how this work gets built, you’ve built something yourself, and you can explain how a solution you propose would work across our systems and services with credibility. You’ll report to the Head of FDE and work closely with AEs, AMs, AI Deployment Strategists, engineering, and Product.

What You’ll Do:

  • Join discovery calls with Account Executives and Account Managers to find the real business problem behind a client’s request.

  • Decide whether the answer is creative talent, a system, or both, and match it to our product portfolio, services, and AI tooling partners.

  • Design the solution architecture, then scope, price, and write the proposal for systems deals, with engineering and studio input.

  • Take every systems deal through the systems review before engineers are assigned.

  • Hand sold work to AI Deployment Strategists for delivery, with clear briefs to engineering and studio teams.

  • Stay close to larger enterprise accounts after the sale as the leadership voice of the original deal.

  • Spot needs that keep recurring and that our portfolio doesn’t cover, and feed them into the product roadmap review.

  • Build reusable sales assets (discovery guides, scoping and pricing templates, proposal modules) and run enablement sessions so AEs and AMs can spot and qualify systems opportunities on their own.

What You’ll Need To Succeed:

  • 3+ years in a client-facing role, such as solutions engineering, technical sales, consulting, product, or forward deployed engineering.

  • Strong consultative selling skills and real customer empathy: you dig into a customer’s needs, problems, and systems before you propose anything.

  • Hands-on experience with agentic software development: you’ve built an agent or a common workflow yourself. You don’t need to be a software engineer.

  • Ability to map out the solution and match available tools to customer problems.

  • A customer-facing or sales background combined with technical depth: you can speak credibly about what the client needs and how it gets delivered.

  • Experience pricing and scoping deals under real timelines, and working with sales, product, and engineering teams.

  • High agency: you take ownership and figure things out.

  • Excellent English verbal and written communication skills.

  • Bonus: enterprise deal experience, performance marketing or adtech, creative industry experience, founding experience, or AI tools for design and creative.

Compensation

Additional Information

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This job listing has been manually reviewed by the Jobicy Trust & Safety Team for compliance with our posting guidelines, including verification of the company's legitimacy, accuracy of job details, clarity of remote work policy, and absence of misleading or fraudulent content.

Role DNA

A quick view of the complexity, pace, ownership and collaboration implied by the job description.

Job Complexity

4/5
EasyHard

Pace & Pressure

4/5
RelaxedFast-paced

Autonomy Level

5/5
GuidedFull ownership

Communication Load

5/5
IndependentCollaborative
AI insightThis role combines pre-sales ownership with enough technical depth to assess agentic AI workflows and produce credible solution architectures. It requires rapid cross-functional coordination, commercial judgment, and the ability to translate ambiguous client problems into deliverable scopes.

Salary analysis

Estimated compensation compared with the broader US market for similar roles.

Estimated job median (per year)Market rate
$135,000
US market range (per year)$110k–$165k
AI insightThe yearly pay period is inferred from the job context; it was not explicitly stated by the employer. No employer compensation was disclosed. The annual figures are inferred USD estimates for a mid-level client-facing AI solutions engineering role in the Canadian market, benchmarked using the configured US analysis market.

Core skills

Skills and capabilities most closely associated with this opportunity.

Sample interview questions
How do you move from an initial client request to a proposed AI solution?

I start with discovery to understand the client’s business objective, current workflow, constraints, data inputs, stakeholders, and success metrics. I then identify whether the best answer is process change, creative services, an AI workflow, or a blended approach, validate feasibility with technical partners, and document scope, assumptions, risks, and measurable outcomes.

Describe an agentic workflow you have built or would build for a creative-services client.

I would define a narrow, measurable workflow first, such as intake and routing of creative briefs. An agent could extract requirements, identify missing details, classify the request, propose an execution path, and route exceptions to a human reviewer, with clear guardrails, audit logs, and quality checks before any customer-facing output.

How would you handle a customer request that is commercially attractive but technically risky?

I would be transparent about the uncertainty rather than overpromise. I would break the request into validated and unvalidated components, engage engineering early, propose a phased proof of value with acceptance criteria, and price the work according to the discovery and delivery effort required.

How do you ensure a sold solution can be delivered successfully after handoff?

I create a complete handoff package covering the customer problem, desired outcomes, agreed scope, technical architecture, assumptions, dependencies, timeline, pricing commitments, and open risks. I also conduct a live handoff with delivery stakeholders and remain available to clarify the original intent for strategic accounts.

What makes a discovery call effective for a technical sales role?

An effective discovery call focuses on the customer’s operating context and business impact, not on demonstrating features too early. I use open questions to uncover workflow pain points, decision criteria, systems involved, stakeholders, urgency, and measurable success outcomes, then summarize my understanding to confirm alignment before proposing a path forward.

This analysis is generated from the job description. Salary estimates, role characteristics and sample answers are guidance, not employer-provided facts.
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