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AI Ads Product Builder/FDE

@ Gigi

Toronto, Ontario

On-siteFull-time
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Overview

Gigi is hiring an AI Ads Product Builder/FDE in Toronto to build and deploy AI-powered ad products and integrations for agency leaders and ads managers. The role is full-time, hands-on software engineering that starts with understanding advertising workflows, and it requires travel to client sites as needed.

Responsibilities:

  • Work directly with agency leaders and ads managers on workflows and needs
  • Design and build features across data, agent logic and interfaces
  • Build integrations with advertising tools and APIs
  • Own client discovery, rollout and follow-through
  • Travel to client locations as needed

Requirements summary:

  • Experience in ad tech and advertising workflows
  • Strong full stack software engineering experience
  • Track record of shipping production software
  • Ability to explain technical choices to non-technical stakeholders
  • Experience with or strong desire to use AI coding tools

Tools & skills

Benefits mentioned

Dental
Source and dates

Employer career site / ATS feed · ashby

Employer posting date
2026-10-01
First seen by our source
2026-10-08
Source record updated
2026-10-09

These dates describe the source record, not a live verification that the employer is still hiring. Check the original posting.

Job details

DepartmentSoftware development
Hours per week40 (estimated)
Travelair: moderate
Work settingOffice, Client sites
PositionMostly sitting
Physical demandsphysical low · computer high
LanguagesEnglish

Summary and details written by AI from the posting; the employer’s posting is the authority.

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Job description

Gigi is the agentic operating system of enterprise media buying. Our first product is the AI media manager for Amazon DSP. Since launching it in summer 2025, we've grown to manage hundreds of millions in advertising spend on behalf of the largest agencies in the world.

We're backed by top venture investors Golden Ventures and Aperiam Ventures. Our founding team has spent 15+ years building in Amazon Ads and ecommerce, including a prior $100M+ exit.

We're hiring an AI Ads Product Builder/FDE to join our engineering team in Toronto. You'll combine advertising domain knowledge, hands-on software development, and client service to build and deploy AI-powered products, workflows, and integrations with Gigi. As a forward deployed engineer, you'll work directly with agency leaders, ads managers, and the teams using what you build.

This is a hands-on software engineering role that starts with understanding the business of advertising. You'll draw on your experience in ad tech and advertising workflows to understand how an agency plans, runs, measures, and reports on campaigns. You'll turn those needs into working software: designing APIs, building interfaces, modelling data, integrating services, testing, and debugging production issues. You'll own the path from a customer conversation to a solution people use in their day-to-day work.

You do not need to be an AI researcher or have years of professional LLM experience. We are looking for a strong software engineer with advertising experience who enjoys helping clients succeed. You'll be comfortable explaining technical choices to nontechnical stakeholders, understanding their business priorities, and following through on delivery. You'll use tools such as Codex, Claude Code, and Cursor as a core part of how you work, while building across agent logic, backend services, data, and the customer-facing product.

As an early employee, you will have a meaningful role in shaping our product, engineering culture, and company.

What you'll do

  • Work directly with agency leaders and ads managers. Understand their business priorities, campaign workflows, reporting needs, and operational challenges. Use your advertising knowledge to ask useful questions, explain possibilities and tradeoffs in plain language, and turn ambiguous needs into a clear problem and a practical solution.

  • Ship end to end. You'll own features from the data layer through the agent logic to the interface a media buyer actually touches. Our stack includes Python, FastAPI, LangGraph and LangChain; TypeScript, Vue and Nuxt; Java and Spring Boot; PostgreSQL, pgvector, Redis and NATS; and AWS.

  • Build with AI as a core part of your development workflow. Use Codex, Claude Code, Cursor, and other coding agents to help plan, implement, test, debug, and review software. You are still responsible for the architecture, quality, and correctness of what gets shipped.

  • Connect Gigi to advertising workflows. Build integrations with the advertising tools, APIs, and data sources customers rely on. Handle permissions, data mapping, failures, and the operational details needed to make a solution work reliably across Gigi and connected systems.

  • Build solutions that strengthen the product. Work with Product and Engineering to decide what should become a shared feature, a reusable integration, or an agency-specific configuration. Solve the immediate customer problem while making future implementations easier.

  • Build reliable agentic systems. You'll learn to design tools, retrieval, memory, evaluations, guardrails, and human approval flows that make Gigi dependable enough to take action inside real advertising accounts. Prior experience with all of these is not expected.

  • Deliver a strong client experience. Own discovery, prototyping, implementation, and rollout in collaboration with customers and the team. Set clear expectations, communicate progress and setbacks, help clients adopt what you build, and follow through when something isn't working. Use feedback and actual workflow results to improve the solution.

  • Work with clients in person. Travel to client locations as needed for discovery, working sessions, onboarding, and rollout support. Build relationships with both agency leaders and the people using Gigi every day.

What success looks like

  • First 30 days. Your code is in production. You've used your advertising experience to understand a customer's workflow, learned how Gigi supports it, and shipped an improvement they can use.

  • Six months. You own a meaningful customer workflow or integration from discovery through production. Agency leaders and ads managers trust you to understand their needs, explain technical decisions clearly, and coordinate delivery with the team.

  • Twelve months. You've shipped something we could not have built without you, turned recurring agency needs into reusable product capabilities, and thrown out at least one thing you built because the abstraction was wrong.

What you'll bring

  • Experience in ad tech and advertising, with practical knowledge of media planning, campaign management, optimization, measurement, and reporting. You understand how agencies and ads managers work and can connect a technical decision to its impact on their business.

  • Client service experience and a strong interest in helping customers succeed. You enjoy building relationships, understanding a client's priorities, responding constructively to feedback, and taking responsibility for follow-through.

  • Strong communication skills with nontechnical stakeholders, including agency leaders and ads managers. You can lead a useful discovery conversation, explain a technical tradeoff without jargon, and set realistic expectations about scope and delivery.

  • A track record of building and shipping production software used by real customers. We care more about what you have built and owned than an exact number of years.

  • Strong full stack software engineering experience. The fundamentals you already have—system design, APIs, data models, interfaces, testing, debugging, and operating production software—transfer directly to this role.

  • Comfort across the stack. Real depth somewhere, no allergy to the parts you're weaker in.

  • Experience using, or a strong desire to become highly effective with, AI coding tools such as Codex, Claude Code, Cursor, or similar tools. You do not need to be an expert on day one, but you should be excited to use them every day—and strong enough technically to review their work, reject weak abstractions, catch missing edge cases, and remain accountable for what ships.

  • Curiosity about how LLMs change software products and the way software gets built. You should be excited to develop good judgment around where AI belongs—and where conventional software is the better answer.

  • Judgment over specification. You can turn an open-ended customer request into a practical scope, set expectations, ship it, and iterate fast when it's wrong.

  • Speed and ownership. LLMs changed what “fast” means for a small team. You should be comfortable using AI coding agents to move quickly while maintaining a high bar for architecture, correctness, and maintainability.

  • Flexibility and willingness to travel to client locations as needed for collaboration, implementation, and relationship building.

What you don't need

  • You do not need an AI research background or experience training foundation models. We build products around existing models, combining them with tools, data, business logic, interfaces, and production infrastructure.

  • You do not need prior experience with every agent framework or concept we use. We expect strong engineers to learn LangGraph, agent orchestration, evaluations, retrieval, and tool use on the job.

  • You do not need a previous Forward Deployed Engineer title. What matters is your ability to combine software development, advertising knowledge, and client service to deliver useful products.

Bonus points if

  • You've built and deployed software for agencies or advertisers, whether as a product engineer, forward deployed engineer, technical founder, or hands-on solutions engineer.

  • You've built integrations with external APIs, enterprise tools, or customer data systems.

  • You've built with LLMs in production: evals, guardrails, tool use, retrieval, agent orchestration, cost and latency work.

  • You have deep hands-on experience with Amazon DSP, retail media, or programmatic advertising platforms.

  • You've built real-time data pipelines at meaningful volume, or been early enough at a startup to know what the first 20 people actually do.

  • You've operated production systems where correctness, permissions, auditability, or customer trust mattered.

The hard parts

We'd rather you know this before you apply.

  • We work hard. We are trying to build a generational company, and early employees should expect intensity, ambiguity, and high standards.

  • Cash compensation is competitive for our stage, but we will not win every late-stage salary comparison. The upside is meaningful ownership and equity in a company growing quickly.

  • We throw out working code when the underlying abstraction is wrong. Some of what you build will not survive, and you'll be the one who calls it.

  • Nobody is siloed. You'll write frontend, debug backend, think through product, join customer calls, and solve whatever problem is blocking the customer.

  • You'll balance time spent building with client conversations, visits, and implementation support. You'll need to stay responsive while being clear about priorities and commitments.


Compensation and equity

  • Base salary: $110k to $200k depending on experience level.

  • Meaningful equity. We want to be as generous with equity as possible, and top performers can expect equity top-ups early and often.

Life at Gigi

  • In-office culture. We work together downtown Toronto, but makers (i.e. engineers) can choose to work where they are most productive on Wednesdays.

  • Catered lunch every day from Toronto's best spots. Current rotation: Impact Kitchen, iQ Food Co., ChopHop, and Cumbrae's.

  • Real snacks: Greek yogurt, Mateína yerba mate, Barebells protein bars, Midday Squares. Tell us what you want and we'll add it.

  • Top-of-the-line Apple equipment.

  • Comprehensive health and dental coverage.

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