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Added 2 mins ago
M&
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- Full-time
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FutureSight

Technical Co-founder (CTO) - AI Collections Agent

Canada

Full-time

Apply About employer

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Job details

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

Original job description

The Opportunity

Finance teams at B2B companies lose cash the same way every month: an invoice ages past 45 days, someone sends an email, no reply, someone calls, voicemail, they call again next week, still nothing. AR teams spend 60–70% of their week on manual follow-up instead of posting cash, closing disputes, or analyzing aging. Adding headcount doesn't fix it; manual follow-up simply doesn't scale, and every ERP hits the same wall.

Problem and solution validation are complete. Live pilots are running with early design partners and entering production evaluation. The next phase is proving in-production reliability, delivery economics, and scalability. The teams that ship credible AI workers into finance-sensitive functions in the next 18 months will define the category. We intend to be one of them.

The Venture

Argentl delivers an AI collections agent that handles outbound debtor follow-up automatically - trained, monitored, and continuously improved by our team. Rather than another self-serve SaaS tool, Argentl is evaluated on outcomes: DSO reduction, hours returned to the AR team, and cash commitments captured - not configuration effort.

Give us a list of overdue accounts and our voice agent calls each debtor, confirms invoice awareness, and captures exactly what they say - a payment commitment, a dispute, a request to split, or silence. The AR team gets a clean morning report: who's committed, who's disputing, who's gone silent, and what to do next. No ERP migration, no system credentials, no workflow overhaul - we're calling within a week of receiving the data. The roadmap expands from collections follow-up into adjacent AI finance-ops roles, all delivered through the same managed model.

The Partnership

The CEO co-founder is in place. The customer thesis is validated, design partners are engaged, and live pilots are running. What remains is to bring on the technical co-founder - a partner who will own product and engineering with the same conviction, urgency, and ownership stake.

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.

Architecture & Reliability - Harden the voice and workflow systems for in-production reliability. Establish core architecture, observability, and audit-trail standards for a product that speaks to customers' debtors on their behalf.
Delivery Layer - Build the internal infrastructure that lets the team configure, monitor, and optimize agent performance without scaling engineering headcount. Mature the workflow engine so every call, intent classification, and next-action flows through reliably.
Integrations & Distribution - Own the accounting and ERP integration layer (QuickBooks, Xero, and beyond) that turns Argentl from a CSV upload into an embedded part of the finance stack - the primary distribution unlock.
Unit Economics - Own the trade-offs between AI quality and cost-per-call, and lock in unit economics within a productized monthly pricing model.
Customer & Market - Represent the company in front of finance leaders, partners, and investors as the technical voice of the venture.
Roadmap - Convert pilots into paying customers, expand the AI staff beyond collections, and begin a path toward custom and self-hosted models where data-privacy and financial-compliance requirements demand it.
Team - Recruit and lead the founding engineering team, and establish the cultural foundation of the company

Co-Founder Profile

Must Have:

Shipped LLM-powered and voice systems into production environments where incorrect outputs carried real consequences
Full-stack confidence across applied LLMs, real-time voice and conversational AI, telephony, human-in-the-loop workflows, observability, and secure multi-tenant SaaS
Well-formed convictions about reliability engineering, edge-case management, and the trade-offs between AI quality and cost-per-call
Experience building managed and service-heavy platforms, with the discipline to scale delivery without scaling engineering headcount
Prepared to operate as a principal - including saying "this won't scale" or "this isn't ready" when the integrity of the product requires it
A hands-on builder - you still write code and ship, and you're happiest close to the product

Great to Have:

Finance, accounting, or FinOps background - you understand AR, DSO, aging, disputes, and how finance teams actually work
Based in Los Angeles or the San Francisco Bay Area (or ready to be)
Pragmatic and creative - a solution finder who gets to "working" fast and iterates from there
Co-operative, strategic, and hands-on in equal measure
Capable and willing to help in finding and closing early customer partnerships
An active social media presence you can put to work for founder-led distribution

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.

Apply About employer

More about this job

Responsibilities

Own product and engineering as a hands-on co-founder, setting technical direction and building reliable voice, workflow, and integration systems for the AI collections agent. Convert pilots into paying customers, establish scalable delivery and unit economics, expand the product roadmap, and recruit and lead the founding engineering team.

Requirements

Candidates must have shipped LLM-powered and voice systems into production where errors have real consequences, with broad expertise across applied AI, telephony, workflows, observability, and secure SaaS. They should be hands-on technical leaders with strong reliability and cost-quality judgment; finance experience, relevant location, and early customer partnership skills are advantageous.

Skills

Applied LLMs
Real-Time Voice AI
Conversational AI
Telephony
Full-Stack Engineering
Reliability Engineering
Workflow Automation
Human-in-the-Loop Systems
Observability
Secure Multi-Tenant SaaS
ERP Integrations
Unit Economics
Engineering Leadership
Product Architecture
Finance Operations

Benefits

Founder-Level Equity
Founder-Level Authority
Co-Decision Rights

Visa sponsorship

Not detected in the job text

Keywords

LLM
Voice AI
Conversational AI
Telephony
Real-Time Systems
Human-in-the-Loop Workflows
Observability
Secure Multi-Tenant SaaS
Reliability Engineering
Edge-Case Management
Workflow Engine
Intent Classification
Audit Trails
QuickBooks
Xero
ERP Integrations
Accounts Receivable
Collections
Days Sales Outstanding
Dispute Management
AI Quality
Cost Per Call
Unit Economics
Managed Platforms
Finance Operations
Data Privacy
Financial Compliance
Self-Hosted Models
Founding Engineering Team

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