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FutureSight

Technical Co-founder (CTO) - AI for Automotive Retail

Canada

Full-time

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Job details

Job type: Full-time
Posting language: English
Posted: Oct 1, 2026

Original job description

The Opportunity

Every used-car dealer's profit is made or lost the moment they buy the car - not when they sell it. That decision runs on gut feel, spreadsheets, and whoever has a spare hour, inside a $500B+ industry that hasn't meaningfully modernized how it buys. We think that's an AI-native category waiting to be built, and we're going first.

The problem and solution are validated with a domain co-founder who lives this daily and has already hand

The Venture

Atrium is an always-on AI workforce, not a dashboard - agents that watch, learn, and earn the right to act on their own, deployed inside dealer groups' existing workflows. The same decision logic has to show up everywhere the work already happens - web, desktop, our own browser, mobile - so the workforce follows the person, not the other way around. One brain, every surface.

This isn't a weekend's worth of CRUD. Think dozens of specialist agents organized into a handful of coordinated workflows, sharing one memory, each one earning the right to act on its own track record - across four surfaces at once. If that sounds like a fun problem rather than a scary one, keep reading.

A real technical moat if built right, and a wide-open field - no dominant AI-native player has claimed this category yet. Specifics on the product, the model, and where we stand commercially are best shared in conversation; we're early and staying deliberately quiet in the market.

The Partnership

CEO and domain co-founder are in place; the problem is validated. We're looking for a technical co-founder to own product and engineering from the first commit - full authority, founder equity, a real seat at the table on every major call.

This is a co-founder role, not a CTO hire. In return for that level of commitment, you receive founder-level equity, founder-level authority with co-decision rights on product, technology, hiring, fundraising, and strategy, and a genuine partnership with the CEO on every material decision.

What You'll Own

As Co-Founder & CTO, you will take over the production code and continue building the product (the first lines of production code), set the technical direction, and lead execution end-to-end.

Own the core architecture decision that shapes everything else - how the agents actually see and act in a dealer's world, and how one system stays coherent across a web app, a desktop app, our own browser, and mobile, without four separate products drifting apart
Design the autonomy model: how an agent earns the right to act alone, and how that trust is never assumed
Build the integration layer into a data ecosystem that won't always cooperate
Build partnerships with ecosystem data providers and third-party systems to land unconventional integrations no standard API gets you
Own unit economics as an architecture problem, not an afterthought - this many agents, across this many surfaces, has to add up
Own the design and layering of the system for the dev team, and keep the build matched to what the business and sales side actually need
Be the technical voice with dealers, design partners, and investors
Hire and lead the founding engineering team

Co-Founder Profile

Must Have:

Has shipped agentic or LLM systems into production where being wrong actually costs something
Has shipped desktop and mobile apps connected to a larger web platform - comfortable with one product living across multiple facets and surfaces, not just a single app
Has shipped LLM-based products, but also worked with SLMs and SLM fine-tuning
Has dealt with the real nuances of web scraping - anti-bot defences, rate limits, brittle DOMs, the gap between "works in a demo" and "works at scale against a site that doesn't want you there"
Has built complex, modelled data graph layers for intelligence - not just a data pipeline, but a structure that reasoning can actually run on
Comfortable owning infra, data, and product alone - then hiring past yourself
Treats guardrails and reversibility as core product, not overhead
Good to have: edge computing and power-constrained systems, high-frequency distributed computing infrastructure

Great to Have:

Experience building against locked-down or adversarial third-party data
Vertical/operational domain grit (Automotive)
Pragmatic and creative - a solution finder who gets to "working" fast and iterates from there
Co-operative, strategic, and hands-on in equal measure

How To Apply

Please submit your resume, LinkedIn profile, and a brief note on why this venture aligns with your goals as a founder. We will move quickly for the right candidate.

FutureSight is committed to diversity, equity, and inclusion. We welcome applicants of all backgrounds and experiences.

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More about this job

Responsibilities

Own product and engineering from the first production code, setting technical direction and building a coherent AI-agent platform across web, desktop, browser, and mobile. Design the autonomy and integration architecture, manage unit economics, represent the technology with dealers and investors, and hire and lead the founding engineering team.

Requirements

The candidate must have shipped production LLM or agentic systems where errors have real consequences, built products across web, desktop, and mobile, and worked with both large and small language models, including fine-tuning. They should also have experience with web scraping and complex data graphs, be able to own infrastructure, data, and product, and treat guardrails and reversibility as core product requirements.

Skills

Agentic AI
Large Language Models
Small Language Models
Small Language Model Fine-Tuning
Web Application Development
Web Scraping
Data Graph Modeling
System Architecture
Cloud Infrastructure
Data Engineering
Third-Party Integrations
Unit Economics
Engineering Leadership
Automotive Retail

Benefits

Founder-Level Equity

Visa sponsorship

Not detected in the job text

Keywords

Artificial Intelligence
Agentic Systems
AI Agents
Large Language Models
Small Language Models
Fine-Tuning
Automotive Retail
Used-Car Dealerships
Web Applications
Desktop Applications
Mobile Applications
Browser Applications
Web Scraping
Anti-Bot Defenses
Rate Limits
Data Graphs
System Architecture
Autonomy Models
Guardrails
Reversibility
Infrastructure
Data Engineering
Third-Party Integrations
Unit Economics
Edge Computing
Distributed Computing
Engineering Leadership
Product Development
Founder Equity

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