Software Engineer, Full Stack

Gigi • Toronto, ON

17d • $110,000 - $200,000 • Hybrid

About The Position

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 doubled revenue in the past two months. We expect to double again by early Q4. We're hiring an AI Builder—a full stack software engineer—to join our engineering team in Toronto and own end-to-end feature development for Gigi, our AI agent. This is still fundamentally a software engineering role. Much of the work will feel familiar: designing APIs, building interfaces, modelling data, integrating services, writing tests, debugging production issues, and making architectural decisions. The main difference is the product we're building: agentic software where LLMs reason, use tools, and take actions on behalf of customers. You do not need to be an AI researcher or have years of professional LLM experience. Strong full stack engineers who are excited to learn how agentic systems work should apply. 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. This is the 12th role at Gigi. As an early employee, you will have a meaningful role in shaping our product, engineering culture, and company.

Requirements

• 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 make a reasoned call, 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.

Nice To Haves

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

Responsibilities

• Ship end to end. You'll own features from the data layer through the agent logic to the interface a media buyer actually touches.
• 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.
• Build the agent's judgment, not just its plumbing. Decide what Gigi should do autonomously and what it must escalate to a human, then score actions on risk and confidence so recommendations read differently when the data is thin.
• Draw the line between probabilistic and deterministic work. LLMs for reasoning, structured software for execution. Knowing where that boundary sits on any given feature is a daily call, not a settled architecture.
• 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.
• Work directly with customers. You'll sit in on calls, read transcripts, and take feedback straight from the media buyers using the product. You'll turn ambiguous customer problems into shipped product without waiting for a perfect spec.

Benefits

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

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: No Education Listed