ATQLeads builds go-to-market systems for B2B companies that are done relying on agencies and can't justify a full-time hire. We fill the gap: a network of vetted GTM operators who work directly inside client teams — in their tools, their Slack, their stack — and are accountable to outcomes, not hours logged.
No retainers. We deploy capacity. Operators are embedded as part of the company. If you want to own real work, run inside real businesses, and be paid like a partner rather than a vendor, you belong here.
Role Overview
The GTM Engineer is the builder at the center of every ATQ Squad engagement.
Without one, strategy stays theoretical. Campaigns stay manual. Data stays siloed. Pipeline stays unpredictable. The GTME converts direction into working operational systems — and keeps them running.
No ticket queue. You get a GTM problem, a client stack, and a capacity commitment. Build the system that solves it. Own its reliability. Drive it forward without waiting to be asked.
What You'll Do
Technical and System Building
Four interconnected systems, owned end-to-end:
Outbound, Inbound, and Pipeline Generation Engine — multi-channel sequences across email, LinkedIn, phone, and video, with channel-appropriate logic. Sending infrastructure and deliverability management: domain warmup, sender rotation, content variation, blacklist monitoring. Inbound capture via webhooks from forms, webinars, intent feeds, and website activity. 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 sources, segmentation, and signal-based targeting using firmographic, technographic, hiring, funding, intent, and behavioral data. Custom signals built from any data source, not just pre-built intent feeds. Composite scoring across multiple signals. Per-source signal expiration and refresh cadence.
Automation and Workflow Layer — end-to-end workflows in Clay (multi-source tables, formula columns, Claygent prompts), Make/n8n (multi-step logic, error handling, retries, webhooks), Apify, and CRM. APIs and webhooks as the default integration method, including when native connectors exist. LLM API calls (Claygent, OpenAI, Anthropic) embedded in production workflows for enrichment, classification, and copy generation. Reusable modules (Clay Functions, Make sub-scenarios) to avoid duplicating logic. Python and pandas for data work no-code tools can't handle.
Conversion Infrastructure — reply handling logic, meeting routing and scheduling flows, CRM hygiene (HubSpot, Zoho, or Salesforce), and tracking and attribution built in from day one, not retrofitted. Dashboards that show conversion rates and volume at each funnel step. Signal source tied to conversion outcome, so you can identify the weakest step and fix it there.
Three Phases of Execution
Foundation — build the initial outbound and data infrastructure, translate the GTM Strategist's ICP into Clay filter logic, configure CRM workflows, and stand up the reporting layer. Define and instrument performance metrics before launch. Deliverable: a functional GTM engine ready to generate pipeline, with monitoring at every step and documentation built alongside — handoff doc, README, Loom walkthrough.
Ongoing — run campaigns, enrich and refresh lead lists, monitor deliverability, manage replies, and keep CRM data accurate (deals move through stages, get deduplicated, and get closed when stale). Track conversion rates at each funnel step (open, reply, positive reply, meeting set, show). Deliverable: consistent campaign execution and steady pipeline flow.
Optimization — A/B test messaging, targeting logic, and conversion paths. Fix the step with the biggest gap between current performance and benchmark — not the one stakeholders bring up most. Expand into new segments and channels once the existing system is stable. Automate any step still requiring manual action. Sharpen ICP definitions using real response and conversion data, not just the original hypothesis. Deliverable: improving efficiency and growing pipeline output.
Cross-Functional Collaboration
Your output depends on quality inputs: ICP definition and positioning from the GTM Strategist, offer clarity and CRM access from the client, clean data from enrichment sources. Weak inputs mean weaker output, so be direct about what you need and when. Actively manage upstream dependencies — flag data quality issues, call out missing Strategist inputs, and ask for clarification when a brief is incomplete.
You work directly with sales, marketing, and growth ops teams as a peer. No jargon. No vendor distance. You're inside the operation, communicating directly with clients — no project manager in between.
Strategic Ownership
After onboarding, you drive your own work. No waiting for a brief. You diagnose problems early — identify which part of the system is underperforming (copy, list quality, deliverability, routing, or timing) and fix it at the source. You prioritize by revenue impact and run experiments that build on each other. Operator mindset: what's the highest-leverage thing to ship this week?
You build systems that outlast your engagement — no required maintenance from the original builder after you leave. The bar is at least one shipped system still running at a past engagement after you moved on.
You'll Thrive Here If You...
1. Have real technical range
Not full-stack, but sharp on:
- Python, JavaScript, or SQL — including pandas for cleaning, deduplicating, and transforming tabular data
- APIs, webhooks, and structured data — default integration approach, even when native connectors 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 web scraping tools (BeautifulSoup, Playwright) when standard enrichment sources fall short
- LLM API integration (Claygent, OpenAI, Anthropic) into production workflows, with prompts that produce reliable, accurate output
- CRM configuration (HubSpot, Zoho, or Salesforce) — workflows, custom objects, lead routing, scoring, bidirectional sync
- Fast debugging, using AI as a co-pilot — not a replacement for judgment
You pick up new tools independently. You solve problems before escalating.
2. Think in outcomes, not tasks
- You ask "why" before you build
- You understand what a qualified lead costs, why conversion rates matter, and how your work ties to a number
- You describe results in outcome terms ("produced X meetings at Y% conversion"), not activity terms ("sent X emails")
- You can explain a multi-step workflow in under a minute
- You communicate in plain language to people focused on results, not tools
- When a decision is challenged, you update it or defend it with reasoning — not just repeat yourself
- You name what you don't know and propose how to fill the gap
- You run your own priorities without being managed
3. Operate like you own it
- You catch a broken funnel before anyone mentions it
- You clean up a process before automating it
- You treat client systems with the same urgency and judgment you'd apply to your own
- You deliver a working artifact within 72 hours of an unstructured brief
- Documentation is part of every deliverable — handoff docs, READMEs, Loom walkthroughs ship with the build, not after
- You account for failure modes (enrichment fallback, deduplication, sync failures, deliverability blacklist) before they cause problems
- Strongest signal we look for: someone who ships something valuable in week one, unprompted
How It Works
This is not a full-time role. You'll be matched to client engagements based on availability and skills, working fractionally inside one or more teams at a time.
Once vetted and onboarded into the ATQ network, you go straight to deployment. From day one you're inside the client's tools — Slack, HubSpot, Notion, Salesforce — operating as part of their team, not as an outside vendor.
Work is scoped through Capacity Units (CUs) — defined outputs with clear scope, not open-ended time blocks. You get paid for what you ship.
Compensation is fair and your reputation compounds across every engagement.
Requirements
Hard requirements
- 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) in production workflows
- CRM configuration on HubSpot, Zoho, or Salesforce — workflows, custom objects, routing, scoring, bidirectional sync
- At least one shipped system still running at a past engagement after you left
- Fluent in English
Working knowledge expected
- Apify or equivalent web scraping (BeautifulSoup, Playwright) when standard enrichment falls short
- Zapier, Retool
- Deliverability ops: domain warmup, sender rotation, content variation, blacklist monitoring
- Composite scoring across firmographic, technographic, hiring, funding, intent, and behavioral signals
- Failure-mode planning: enrichment fallback, deduplication, sync failures, deliverability blacklist
- pandas for tabular data cleaning and transformation
How you work
- Async-first: Slack, Notion, Linear
- Working artifact delivered within 72 hours of an unstructured brief
- Documentation ships with every build (handoff doc, README, Loom)
- Direct client communication — no PM layer
- Self-managed priorities and blockers
- Upstream issues get flagged, not worked around
Benefits
- Fully remote
- Work on your own schedule
If you want to do the best work of your career building the next generation of AI-powered GTM systems, this is the role.
Job Type: Contract
Pay: $662.00 - $993.00 per hour
Work Location: Remote
