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Added 5 months ago
H
Automation Engineer - Workflow & Process Automation
Huzzle
Remote, Canada
- Full-time
- Remote
At Huzzle, we connect high-performing professionals with global companies across the UK, US, Canada, Europe, and Australia. Our clients include startups, digital agencies, and tech…
Added 5 months ago
S
Associate AI Engineer
ShyftLabs
Toronto, Ontario
- Full-time
Proficiency in Python and familiarity with libraries or frameworks such as TensorFlow, PyTorch, or Scikit-learn
Added 6 months ago
A
Go-to-Market Engineer
atqleads
Remote, Canada
- Contract
- Remote
The GTM Engineer is the engine builder at the core of every ATQ Squad engagement.
Added 6 months ago
D
Software Engineer, Detection (TOR)
Doppel
Toronto, ON
- $157,000 to $367,000 CAD / year
- Full-time
Strong mastery of at least one backend language (Python, Go, Java, or Node) and comfort with web APIs, async processing, and service frameworks.
Added 2 months ago
Sr. Staff Physical Design Timing Engineer (STA)
Lightmatter
Toronto, ON
Well versed with scripting languages like TCL and Python, PERL, or Shell
Added 2 months ago
Data Platform Operations Engineer
Scotiabank
Toronto, ON
The Data Platform Operations Engineer works under the guidance of senior engineers and platform leads to help maintain site reliability for our Data & AI platforms. This role focuses on…
Added 6 months ago
Network Engineer, Foundation and Support (Edge/Backbone Infrastructure Design)
Meta
Quinte West, Ontario
…this role, we are looking for a Network Infrastructure Design Engineer with demonstrated experience in developing and delivering network infrastructure solutions at scale in a data center…
Added 1 month ago
M
DevSecOps Engineer
Maxima
Toronto, ON
- Full-time
We are working on some of the hardest problems in enterprise automation, with an engineering team that includes staff-level talent from Robinhood, Glean, Google, Netflix, and Meta. The…
Added 6 months ago
S
Senior Software Engineer II
SurveyMonkey
Remote, Canada
- $126,400 to $158,000 CAD / year
- Full-time
- Remote
Expert-level Python skills and experience with high-scale data processing (PySpark, etc.).
Added 6 months ago
GS
Senior Site Reliability Engineer
Guidewire Software
Remote, Canada
- Full-time
- Remote
…great people. We’re searching for a Senior Site Reliability Engineer who not only brings deep technical expertise but also thrives on engaging with customers, partners, and cross-functional…
Added 6 months ago
B
Machine Learning Engineer, Underwriting
Bree
Remote, Canada
- $180,000 to $250,000 CAD / year
- Full-time
- Remote
Proficiency in Python and familiarity with ML libraries like Scikit-learn, LightGBM, and PyTorch.
Added 6 months ago
H
AI Engineer - Remote
Huzzle
Remote, Canada
- Full-time
- Remote
We are looking for a highly skilled AI Engineer to design, build, and deploy AI-driven applications and machine learning solutions. You’ll work closely with product, engineering, and data…
Added 6 months ago
SA
Machine Learning Engineer
Sanctuary AI
Vancouver, British Columbia
- Full-time
…training and running ML policies on robots, and working closely with researchers to implement and deploy novel ML techniques into production. With access to our in-house robotic platforms,…
Added 4 months ago
RA
Staff Embedded Software Engineer, VCS
Rivian and Volkswagen Group Technologies
Remote, Canada
- $137,300 to $171,600 CAD / year
- Full-time
- Remote
Rivian and Volkswagen Group Technologies is a joint venture between two industry leaders with a clear vision for automotive’s next chapter. From operating systems to zonal controllers to…
Added 6 months ago
A
Field Engineering Co-Op
Acceldata
Kitchener, Ontario
- Internship
As a Field Engineer Co-op at Acceldata, you’ll be working hands-on with complex distributed systems, helping real customers solve deep infrastructure and data observability challenges.
Added 6 months ago
A
Sales Engineering Co-Op
Acceldata
Kitchener, Ontario
- Internship
As a Sales Engineer Co-op at Acceldata Inc, you will work closely with our sales engineering team to support customer-facing initiatives across solution design, pre-sales, and technical…
Added 6 months ago
T
Machine Learning Engineer II
TD
Remote, Canada
- Full-time
- Remote
As a candidate, you are encouraged to ask compensation related questions and have an open dialogue with your recruiter who can provide you more specific details for this role.
Added 6 months ago
W
Senior / Staff ML Training Optimization Engineer
Waabi
Toronto, ON
- Full-time
Waabi, founded by AI visionary Raquel Urtasun, is the leader in Physical AI. With a world-class team, we're unlocking the next era of autonomous transportation with technology that's…
Added 2 months ago
W
Senior Software Engineer - Evisort AI (Python/Typescript)
Workday
Remote, Canada
- Full-time
- Remote
Evisort Engineering is growing! As a Senior Backend Software Engineer, you'll join a collaborative, cross-functional team working to enhance and expand our AI-driven contract management…
Added 2 months ago
IT Industrial CrossFunction - Full Stack & AI Integration
Amrize
Mississauga, ON · Laval, QC
The Industrial IT Full Stack / Back End & AI Integration Snr. Engineer role is to contribute her/his skills to the development of company Industrial Solutions including AI-powered features…
Added 6 months ago
O
Staff Software Engineer
OpenMined
Remote, Canada
- Full-time
- Remote
…engineering standards by example. You're the most experienced engineer on the squad, the person others look to for production-quality judgment, and the voice that connects this team's…
Added 3 months ago
NS
IC Design Verification Engineer
NXP Semiconductors
Ottawa, Ontario · Kanata
- Full-time
We are seeking a highly motivated Design Verification Engineer with a relentless drive to excel and make a significant impact. Our team offers innovative thinking, engineering expertise,…
Added 6 months ago
S
Senior Full Stack Software Engineer
Super.com
Remote, Canada
- Full-time
- Remote
As a Senior Full-Stack Engineer, you will be a senior technical contributor on one of our teams, working across both frontend and backend web development. You will help solve complex…
Added 2 months ago
Developer, Platform Engineering
Scotiabank
Toronto, ON
The Platform Engineer will work under the guidance of Sr Engineers/Platform Leads to build, tune, manage infrastructure, DevOps, monitor troubleshoot, enhance, enable new features & provide…
Added 6 months ago
Sr Cloud Platform Engineer WOTC
Hasbro
Montreal, Quebec
We are seeking a Senior Cloud Platform Engineer to join our Central Technology Build Engineering team as we develop and curate an Unreal Engine ecosystem to share across our internal game…

atqleads

Go-to-Market Engineer

Remote, Canada

Remote

Contract

Apply About employer

Applications open in a new tab.

Job details

Job type: Contract
Workplace: Remote
Posting language: English
Posted: May 7, 2026

Original job description

This is a remote position.

ATQLeads builds GTM systems for B2B companies that are done waiting on agencies and tired of the cost of full-time hires. We sit between the two: a network of vetted GTM operators who embed directly inside client teams - inside their tools, their Slack, their stack - and deliver against outcomes, not hours.

We don't sell retainers. We deploy capacity. Operators are part of the company. If you want to own real work, operate inside real companies, and be compensated like a partner rather than a contractor, this is where you belong.

Role Overview

The GTM Engineer is the engine builder at the core of every ATQ Squad engagement.

Strategy without a GTME stays theoretical. Campaigns stay manual. Data stays fragmented. Pipeline stays unpredictable. The GTME is the person who turns direction into operational machinery and then keeps that machinery running.

You won't be assigned tickets. You'll be given a GTM problem, a client stack, and a capacity commitment. Your job is to build the system that solves it, own its reliability, and push it forward without being asked.

What You'll Do

Technical and System Building

You own four interconnected systems end-to-end:

Outbound, Inbound and Pipeline Generation Engine - multi-channel sequences across email, LinkedIn, phone, and video, with sequence logic appropriate to each channel. Sending infrastructure and deliverability management: domain warmup, sender rotation, content variation, blacklist monitoring. Inbound capture via webhooks from forms, webinars, intent feeds, and website behavior. Product-led activation flows (signup → first key product action → conversion trigger) when product event data is available.

Data and Enrichment System - lead sourcing, TAM mapping, waterfall enrichment across multiple data sources, segmentation, and signal-based targeting using firmographic, technographic, hiring, funding, intent, and behavioral signals. Custom signals built from any data source, not only pre-built intent feeds. Composite scoring models that combine multiple signals. Signal expiration and refresh cadence management per source.

Automation and Workflow Layer - end-to-end workflows across Clay (multi-source tables, formula columns, Claygent prompts), Make/n8n (multi-step logic, error handling, retries, webhooks), Apify, and CRM. API and webhook integrations as the default approach, including when native integrations exist. LLM API calls (Claygent, OpenAI, Anthropic) integrated into production workflows for enrichment, classification, or copy generation. Reusable modules (Clay Functions, Make sub-scenarios) so logic is not duplicated across tables. Python and pandas for data work no-code tools cannot handle.

Conversion Infrastructure - reply handling logic, meeting routing and scheduling flows, CRM hygiene (HubSpot, Zoho, or Salesforce), and tracking and attribution infrastructure built in at system setup, not added afterward. Dashboards that show conversion rates and volume at each funnel step. Signal source mapped to conversion outcome, so you can identify the step with the largest performance gap and fix it there.

Three Phases of Execution

Your work runs in three modes depending on where the engagement is:

Foundation - build the initial outbound and data infrastructure, translate the GTM Strategist's ICP into Clay filter logic, configure CRM workflows, and establish the reporting layer. Define and instrument the metrics needed to evaluate system performance before launch. Deliverable: one functional GTM engine ready to generate pipeline, with monitoring at each step and documentation alongside the build - handoff doc, README, Loom walkthrough.

Ongoing - launch and manage campaigns, enrich and refresh lead lists, monitor deliverability, handle replies, and maintain CRM accuracy (deals progress through stages, are moved, deduplicated, and closed when stale). Calculate conversion rates at each funnel step (open, reply, positive reply, meeting set, show). Deliverable: consistent campaign execution and pipeline flow.

Optimization - A/B test messaging, targeting logic, and conversion paths. Prioritize improvements at the funnel step with the largest gap between current performance and benchmark, not by stakeholder requests. Expand into new segments and channels once the existing system delivers consistently. Reduce manual steps systematically by automating any step still requiring human action. Refine ICP using actual response and conversion data, not only the initial hypothesis. Deliverable: improving efficiency and scaling pipeline generation.

Cross-Functional Collaboration

You depend on inputs to do your job well: ICP definition and positioning from the GTM Strategist, offer clarity and CRM access from the client, and clean data from your enrichment sources. Weak inputs reduce output efficiency, so you'll need to be direct about what you need and when. Manage upstream dependencies actively: report data quality issues, flag missing Strategist inputs, and request clarification when a brief lacks the inputs needed for accurate delivery.

You'll work closely with sales, marketing, and growth ops teams as a peer. No jargon. No vendor distance. You're inside the operation. You communicate directly with clients without a project manager intermediary.

Strategic Ownership

After onboarding, you generate your own ideas. You don't wait for a brief. You diagnose bottlenecks early - identify which step of the system is causing performance issues (copy, list quality, deliverability, routing, or timing) and resolve at that step. You prioritize by revenue impact and build experiments that compound. You think like an operator: what's the highest-leverage thing to ship this week?

You build systems that continue functioning after you leave the engagement, with no required maintenance from the original builder. A track record of at least one shipped system still running at a previous engagement after you left is the bar.

You'll Thrive Here If You...

1. Have real technical range

You don't need to be full-stack, but you need to be sharp with:

Python, JavaScript, or SQL - including pandas for cleaning, deduplicating, and transforming CSV/Excel data
APIs, webhooks, and structured data - used as the default approach, including when native integrations exist
Clay (required) - multi-source tables, waterfall enrichment, formula columns, Claygent prompts
Make (preferred) or n8n - multi-step scenarios with error handling, retries, and webhooks
Zapier, Retool, Apify, and equivalent web scraping tools (BeautifulSoup, Playwright) when standard enrichment sources do not return the required data
LLM API integration (Claygent, OpenAI, Anthropic) into production workflows, with prompts that produce consistent and accurate output
CRM configuration (HubSpot, Zoho, or Salesforce) - workflows, custom objects, lead routing, lead scoring, bidirectional sync
Debugging fast and using AI as a co-pilot, not a crutch

You learn new tools on your own. You figure things out before asking.

2. Think in outcomes, not tasks

You ask "why" before building something
You know what a qualified lead costs, why conversion rates matter, and how your work connects to a number
You describe your work in outcome terms ("produced X meetings via Y% conversion"), not activity terms ("sent X emails")
You can explain a multi-step workflow in 60 seconds
You communicate in plain language to people who care about results, not your stack
When a technical decision is challenged, you revise it or add reasoning - you don't restate the original answer
You acknowledge gaps in your knowledge and propose how to resolve them
You manage your own priorities without being managed

3. Operate like you own it

You can spot a broken funnel before anyone tells you
You improve a process before you automate it
You treat client systems like your own, with urgency, ownership, and judgment
You deliver a working artifact within 72 hours of an unstructured brief
Documentation ships with every deliverable - handoff docs, READMEs, Loom walkthroughs are part of the build, not an afterthought
You plan for failure modes (enrichment fallback, deduplication, sync failures, deliverability blacklist) before they break the system
The best signal we look for: operators who ship something valuable in week one, without being asked

How It Works

This is not a full-time role. You'll be matched to client engagements based on your availability and skill fit, working fractionally inside one or more client teams at a time.

Once you're vetted and onboarded into the ATQ network, deployment is the next step. From day one, you're embedded inside the client's tools: Slack, HubSpot, Notion, Salesforce. You operate as part of their team, not as an outside vendor.

Work is structured around Capacity Units (CUs) - defined outputs with clear scope, not open-ended time commitments. You are paid for what you ship.

With ATQ, you are paid fairly and your reputation travels with us across every project.

Requirements

Hard requirements (must have)

Clay - multi-source tables, waterfall enrichment, formula columns, Claygent prompts
Make or n8n - multi-step scenarios with error handling, retries, webhooks
Python, JavaScript, or SQL (at least one)
APIs and webhooks as the default integration approach
LLM API integration (Claygent, OpenAI, or Anthropic) into production workflows
CRM configuration on HubSpot, Zoho, or Salesforce - workflows, custom objects, routing, scoring, bidirectional sync
Track record: at least one shipped system still running at a previous engagement after you left
Fluent in English

Working knowledge expected

Apify or equivalent web scraping (BeautifulSoup, Playwright) when standard enrichment fails
Zapier, Retool
Deliverability ops: domain warmup, sender rotation, content variation, blacklist monitoring
Composite scoring across firmographic, technographic, hiring, funding, intent, behavioral signals
Failure-mode planning: enrichment fallback, deduplication, sync failures, deliverability blacklist
pandas for CSV/Excel cleaning and transformation

Operating requirements

Async-first work in Slack, Notion, Linear
Deliver a working artifact within 72 hours of an unstructured brief
Ship documentation with every build (handoff doc, README, Loom)
Communicate directly with clients - no PM intermediary
Manage your own priorities and blockers
Report upstream data and strategy quality issues, don't work around them

Benefits

Fully remote work environment
Freedom to work whenever you want

If you want to do the best work of your career while shaping the next generation of AI-powered go-to-market systems, this role is for you.

Apply About employer

More about this job

Responsibilities

Build and maintain automated go-to-market systems including outbound, inbound, and data enrichment engines. Optimize conversion funnels and manage technical infrastructure to generate predictable B2B pipelines for clients.

Requirements

Must have expertise in Clay, Make/n8n, and at least one programming language (Python, JS, or SQL) for data transformation. Requires a proven track record of shipping functional GTM systems and experience with CRM configuration and LLM API integrations.

Skills

Clay
Make
n8n
Python
JavaScript
SQL
API Integration
Webhooks
CRM Configuration
LLM API Integration
Web Scraping
Data Enrichment
Deliverability Management
Pandas
Workflow Automation
Lead Scoring

Benefits

Fully Remote Work Environment
Flexible Working Hours

Remote locations

Montreal, QC, Canada

Remote locations (standardized)

Montréal, Quebec, Canada

Visa sponsorship

Not detected in the job text

Keywords

Go-to-Market
B2B
Clay
Make
n8n
Python
Pandas
SQL
JavaScript
HubSpot
Salesforce
Zoho
OpenAI
Anthropic
Apify
BeautifulSoup
Playwright
Zapier
Retool
API
Webhooks
Lead Sourcing
TAM Mapping
Deliverability
CRM Hygiene
Conversion Rate Optimization
Product-Led Activation
Waterfall Enrichment
Composite Scoring
Async-first

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