15 Comments

So a GTM Engineer is business savvy, understands the customer journey, ICP, and business model, with technical skills of data and SaaS management, knows how to collect, clean, and mine customer data from large datasets, and use them for business purposes like messaging personalization and distribution, can comfortably jump into, learn, and master multiple SaaS tools, and also code?

Oh and they know multiple AI models — Perplexity, Llama, OpenAI, etc. — and know how to scope them and leverage different use cases to deploy scraping, scoring, routing, personalization and inject efficiency and scalability to the GTM motion?

Does this unicorn exist in our current reality or are we chasing another hot trend? Asking for a friend.

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I agree it's not an easy one — just gave you 10+ examples of profiles that fit the bill and teams that have that approach. They're probably just a portion of what's out there :)

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He I am!

I've been doing this for years now.

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I think that the GTM Engineer could exist only in small/mid early-stage context.

When you scale, you need vertical expertise.

When you’re trying to reach PMF, you have low resources and so you need people with horizontal skills.

Personal opinion :)

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Could very well be true — also because larger orgs have less growth mindset, less velocity, and knowledge of modular stacks, which attract less this kind of talent

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Where do you go to learn and take courses to become a GTM engineer?

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Try to start here: https://www.getcargo.io/community

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I’ve got a GTM background and already use tools like Clay and Apify, but I want to level up my tech skills. You said Ironhack, Le Wagon, or Codesmith.io. Which one’s worth it? And where would you even start?

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@maxdevil what are your thoughts on this one? You should also check out the first community of GTM engineers here: https://www.getcargo.io/community

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Thanks, Matteo! That was quick—I already applied this morning.

Here’s why I’m asking:

I need to gather job data (LinkedIn, Indeed, etc) and break it down: number of openings, benefits, in-office vs. operational roles (drivers, retail, etc.) for scoring, and actionable info for SDRs/AEs.

I’m trying to learn machine learning to build predictive account/lead scoring systems based on traits of great customers (high LTV, ACV, low churn) to create better account lists.

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I'm pretty sure you could do this with Clay alone.

- Scrape LinkedIn company pages hiring job = SDR/AE

- Use ClayAgent to enrich each listing with metadata (eg. benefits, etc.)

- Score each job based on your criteria

Not sure I got your task right though, but you could play around with Clay? :D

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Didn't think about ClayAgent for that. I’ll give it a try. Thanks!

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The future of marketing!

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Great post on GTM Engineers. I’m one at Clay and have a newsletter focused GTM Engineering for anyone interested in how to guides, how to use Clay, and AI in GTM: claymation.io

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8dEdited

Truth is: If it would work as perfect as promised, those magical vendors would offer a performance-based billing model where they get paid if they deliver the results that they promise via LinkedIn and Email. No one is doing that - thus it is all a huge portion of GTM savvy self-marketing. Specifically B2B SaaS which is not product led is tricky... low subscription B2B SaaS Sales is no magic at all

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