Live opening · Posted 5 days ago

GTM Engineer

de Anda Capital · United States (Remote)
Linkedin Yes
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At a glance

The key details from the original listing.

Posted 5 days ago
Companyde Anda Capital
LocationUnited States (Remote)
Work modeYes
SourceLinkedin
Listed5 days ago

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About the role

Description supplied by the original job listing.

Start Date: Flexible — to be agreed with the selected candidate
Type: Full-Time — Paid (approximately 40 hours/week)
Location: Remote (global), with at least three agreed hours of overlap during 9 a.m.–5 p.m. New York time
Compensation: USD 1,000–5,000/month
Please read until the end for complete instructions on how to apply. Shortlisted candidates complete a paid Loom review of our real deal-origination funnel.
About Us
de Anda acquires businesses and helps its portfolio companies grow. Finding the right companies, qualifying them against our acquisition thesis and starting credible conversations with their owners is central to how we work — and this role owns the system that does it.
Your work will support both deal origination and growth across our portfolio businesses, so you'll see a range of markets and commercial problems, and you'll see directly how the team uses what you build and what comes back from the market.
Role Overview
You'll help decide how we find companies, which owners we approach and what we say to them. You'll use AI to research companies, develop qualification logic, build automations and improve messaging — then decide what information matters, check the outputs and keep improving the system based on real responses.
AI-assisted research, workflow generation and iteration are the default way of working here. You remain responsible for the inputs, the decisions, the evidence, the costs and the results. This is not a junior execution role: you'll review what exists, challenge the approach and own what happens next.
Ideal Candidate
You have GTM ideas you want to try, and you'd rather own a system than operate someone else's.
You spot a commercial opportunity, pick the data and tools to pursue it, direct AI to do the research and build, and then judge honestly whether the result is useful.
You keep experimenting with new AI capabilities and can explain which ones earned a place in your workflow and which didn't.
You find useful data other people miss and turn it into a relevant reason for someone to talk to you.
You work independently and communicate concisely in writing, especially asynchronously.
Responsibilities
Data Sourcing & Research
Evaluate and combine databases, public sources and AI research to find acquisition targets that fit the thesis.
Choose sources for useful coverage, evidence and freshness, and compare that coverage against cost.
Verify company identity, ownership and the right contact before anyone is approached.
Qualification & Filtering
Turn the buy box into a qualification system: hard exclusions, ranking signals and cases that need more research.
Give AI the criteria, examples and evidence standards it needs, and test both accepted and rejected records so good targets aren't quietly missed.
Keep company fit separate from evidence that an owner actually wants to sell, and handle missing information deliberately.
Messaging & Outreach
Connect a segment and an owner-specific fact to a credible reason to talk.
Direct AI to develop and adapt messaging, inspect samples, and improve it using real owner responses.
Supply qualified opportunities to the sales and analyst team through a reliable, repeatable process.
Workflow Build & Feedback Loop
Direct AI to build and operate workflows using natural-language workflow builders, research agents and AI-generated integrations — choosing the simplest approach that can be checked and maintained.
Diagnose bad output by understanding where information enters, which decisions are made and which actions follow.
Use analyst dispositions, owner replies and qualified conversations to improve sourcing, filters and messages, testing one meaningful change on a reviewed sample before expanding it.
Track quality, cost and time saved alongside commercial results, and document what improved, what didn't and why.
Requirements
Examples of GTM work you've delivered with AI and tools such as Clay (or comparable research/enrichment workflows), including how you chose the data, directed the AI, caught bad output and judged the result.
Sound judgment about data sources, entity and contact matching, qualification and uncertainty.
Ability to write, or direct AI toward, credible messaging that gives the recipient a reason to engage.
Ability to inspect a workflow, identify why it is producing bad results and direct the fix.
Clear written and spoken English.
Full-time availability (approximately 40 hours/week) with at least three agreed hours of overlap during 9 a.m.–5 p.m. New York time.
Self-directed in a remote setting, with concise asynchronous communication.
Preferred Qualifications
Experience with acquisition sourcing, deal origination or reaching out to business owners.
Hands-on use of natural-language workflow builders and research agents (for example Clay's Sculptor or n8n's AI Workflow Builder) — examples of the working method, not a mandatory stack.
A track record of trying new AI capabilities in live GTM work and measuring whether they helped.
A particular degree or traditional software-engineering background isn't required. Writing code by hand isn't either: when a custom integration is needed, you should be able to direct AI to create it and check its behavior.
What You'll Gain
Ownership. Room to shape the system: review what exists, challenge the approach and decide how our sourcing, filtering and messaging improve.
Freedom to choose your tools. Bring the AI agents, research tools and workflow builders you like, with latitude to test alternatives within an agreed budget.
Problems with real stakes. Work on finding acquisition targets and helping portfolio companies grow, and see how your work is used and what the market says back.
Range. A useful approach in one market becomes the starting point for the next, so you build systems that improve as you learn.
How to apply
Step 1 — Apply on LinkedIn and you will recieve an email request to send a GTM workflow you've delivered, what you used AI for, and what you learned.
Step 2 — Short introduction. A 20-minute conversation about one real workflow you've delivered: your decisions, what AI did and how you judged the result.
Step 3 — Paid Loom review. Selected candidates receive our current deal-origination funnel and record a 10–15 minute Loom with feedback on its data sourcing, filtering and messaging, plus your top priorities and how you'd use AI to execute them. We pay USD 150 for a good-faith submission, with up to 90 minutes of total preparation and recording. Use AI as part of your process. No implementation, code or written report is required.
Step 4 — Discussion. A conversation about your recommendations and tradeoffs, plus a relevant past project. No coding test or surprise build assignment.

Work arrangement
Yes

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