Senior Product Engineer

SELLIT9; Toronto; On-site; CAD 120,000 - 160,000; Full time

Job summary

SELLIT9 is seeking an engineering leader to design schemas, build APIs, ship UI, and operate production systems on GCP. You will own the product questions behind your work, turning them into specs and end-to-end solutions that move metrics.

You will sit between product, design, and engineering, owning tickets and shaping the design system in code while delivering for both people and AI agents. You will extend agent surfaces and automateoperations with agents.

Qualifications

• 5+ years building and running production systems with modern web stacks.
• Proficient with TypeScript, Node.js, React/Next.js, and PostgreSQL in production.
• Experience designing and shipping production APIs and integrations, ideally on serverless GCP.
• Ability to own features end-to-end from spec to metrics and impact.

Responsibilities

• Own features end to end: spec, database schema, APIs, UI, tests, deployment, and metrics.
• Build systems behind pricing, data ingestion, and calibration reports.
• Ship customer-facing product across quote, checkout, and merchant flows.
• Design and implement APIs and integrations for merchant partners (Shopify, Magento).
• Own the product side: write specs, scope MVPs, prioritize work, and defend metrics.

Skills

TypeScript

Node.js

React/Next.js

PostgreSQL

GCP

API design

AI-native development

Design sense

Tools

Shopify

Magento

Job description

About the Role

This is an engineering role first. You'll design schemas, build APIs, ship UI, and operate production systems on GCP, and you'll be judged on the quality of what you ship. On top of that foundation you'll own the product side of your work too: you'll take a product question ("why did this model stop converting?"), turn it into a spec, build it end to end, and watch the metric move. A recent example: our market-prices system, where one engineer owns everything from the scraper data contract to the calibration report that tells us when a rival outbids us.

The role sits deliberately between product, design, and engineering. There's no separate PM writing your tickets. Our design system lives in code, so you'll make the design calls and ship polished UI without waiting for a handoff. And you'll build for two kinds of users: people and AI agents. Our trade-in flow already runs inside Claude through our MCP connector, and a growing share of our operations run as agent workflows the team writes as skills.

A note on AI-native: AI multiplies engineering skill, it doesn't replace it. You need the depth to review, correct, and own everything an agent writes, because you could have written it yourself. Vibe coding doesn't survive contact with a production pricing system.

What You’ll Do

• Own features end to end: spec, Postgres schema, NestJS and Cloud Functions APIs, Next.js UI, tests (Jest, Playwright), deployment, and the metric afterwards.
• Build the systems behind pricing: market-data ingestion with dry-run validation, append-only observation datasets, and calibration reports ranked by competitor gap.
• Ship customer-facing product across the quote, checkout, and merchant-embedded flows.
• Design and implement APIs and integrations for merchant partners (Shopify, Magento, any custom API integration).
• Do the product job for what you build, prioritizing directly with the CTO.
• Extend our agent surface: write skills and plugins for the team, build MCP servers for internal tools, and improve the public Claude connector.
• Automate operations with agents: alert triage, changelogs, reports, data checks. If you do something twice, you teach an agent to do it.

Apply if you

• Have 5+ years of professional experience building and running production systems with TypeScript, Node.js, React/Next.js, and PostgreSQL. Real systems with real users, not demos or prototypes.
• Have built and shipped production APIs and integrations, ideally on serverless GCP (AWS also valuable).
• Care about data modeling: you understand why append-only tables, point-in-time correctness, and partitioning matter for data that will train models later.
• Work AI-natively, and this is non-negotiable: agentic coding tools (Claude Code, Codex, or similar) are your daily driver, you write your own skills, plugins, and MCP servers, and you can defend every line an agent writes.
• Have product sense: you can write a spec, scope an MVP, challenge a prioritization call, and own a metric.
• Have design sensibility: you sweat UI details and can ship a polished interface from a design system without a handoff.

Even better if you have

• Machine learning experience. The market-price dataset is built to be trained on, and you'd partner with the ML seat that owns pricing calibration.
• LLM product features in production: tool use, structured outputs, evals.
• Experience in e-commerce, fintech, or marketplaces.