How to Get into Sales Tech: The Fastest-Growing Role in Tech That Isn’t Taught at University
You’ve spent years on the side where things are built. Product, architecture, infrastructure. The work that makes it all tick. Down the corridor, or on another floor, or on that call from another city, there they were: closing deals, talking about revenue, forecasts, growth, and key accounts. A parallel world with its own language, its own metrics and its own rules: ‘the sales floor’.
If you’ve ever wondered how that world works from the inside: this is what it’s all about.
Building good software is complex; selling it is too
Over 40% of roles in a tech company are sales-related: BDR, Account Executive, SDR, Partnerships Manager, Customer Success. Creating good software is complex; selling it is too. It’s no longer just a guy taking you out for lunch to convince you to buy his software; there’s a whole highly professionalised structure built around sales. Sales today have nothing to do with what you probably have in mind.
But there’s something more specific worth mentioning: if you look at the local offices of the best-known tech companies, not the headquarters or product hubs, but the country offices, the pattern is always the same. Google Madrid, TikTok Spain, Anthropic in most of the europe local offices, ElevenLabs here. What are they hiring for? Sales. Almost exclusively sales. The engineering is in San Francisco, in London, in Dublin. The go-to-market is here. So, if you’re in Spain and want to work at one of those companies, sales roles are the gateway.
What makes your engineering background particularly valuable here
There is something that generalist sales roles lack, but which an engineer keen to move into sales does have: technical knowledge and credibility.
When a client asks “how does this work under load?” or “how does this integrate with our current stack?”, most Account Executives improvise or escalate to the solutions team. The best ones do not.
Someone who truly understands the product can answer on the spot, without any downtime. The impression you convey to the client is very different.
That closes deals. And it closes deals much faster.
The role of Solutions Engineer or Pre-Sales Engineer exists precisely for that: to bridge the gap between what the product does and what the client needs. And it is one of the best-paid roles in the sales structure of any tech company.
But what if you don’t want to do demos? What if you don’t want that much customer contact?
Not all roles are the same or involve direct customer contact; not all of them are ‘field’ roles.
You could look into Strategy & Go-to-market, Partnerships or Product-Led Growth. Roles where the job is to identify which markets to target, which partnerships to build, and how to scale product adoption without relying solely on the direct sales team.
Your engineering mindset, that problem-solving ability honed by your day-to-day work as a developer or engineer, will come in very handy. Bear in mind that most people in these roles have a generalist background.
Now, it’s not all plain sailing: selling well is difficult. More so than it appears from the outside. It requires reading people, strategy, empathy, analysis, managing relationships that don’t always go smoothly, resilience, and many other things that aren’t learnt in a course, they’re learnt the hard way.
When someone with a technical background develops or possesses these skills, you hit the jackpot.
How far can AI go in sales roles?
AI can write prospecting emails, conduct account research, generate proposals and analyse purchase intent. It can handle the routine tasks of a junior sales role in a matter of seconds.
What it cannot do is sit down with a company’s CTO and have a complex technical discussion. It cannot detect that the person on the other end of the call is concerned about data migration, even if they haven’t said so explicitly. It cannot build the trust that makes someone decide to switch providers after five years.
And above all, what AI will not do is empathise with the customer.
Technical professionals moving into the commercial side will be the ones who face the toughest competition from AI, precisely because they excel at what AI cannot: combining technical judgement with human connection.
Tips for making the leap
First, do your homework; don’t just say, “I want to switch to sales”. Which industry? What kind of role? Big tech, a scale-up or a consultancy?
And here’s an important decision to make: if you really want to learn sales, you basically have two paths:
a) Join a big tech hub, where processes are defined, training is structured, and the name on your CV opens doors.
b) Join a scale-up or start-up, where you’ll learn faster, have more autonomy from day one, and your impact will be visible straight away. They are different experiences. Neither is better in the abstract; it depends on what you need right now.
c) Go to a consultancy firm, where there are usually more opportunities and it can be an easier route into the role. You’ll have to adapt to a fast-changing environment with many different clients.
Then comes networking. Not when you’re actively looking, but right now. Map out who in your network is already working in commercial roles in tech, who is at companies that interest you, and who might mention your name in a conversation. An internal referral during the selection process for a transitional role is worth more than any cover letter. Work on your own storytelling before you start knocking on doors, in other words, create your own sales pitch 😉
Think of your transition from tech to non-tech as a sales process. You define your strategy, identify your target audience, build relationships before you need them, secure meetings with decision-makers, and close your own deal…
One more thing
A key difference when you move into sales is that the impact is measurable; everything in sales is measured down to the last detail. There is less room for ambiguity, and those metrics are visible. Salary growth is linked to that performance, and your seniority or the knowledge you can bring to the table matters less. People coming from a tech background are used to working with metrics, and this shouldn’t be a problem, but it is a paradigm shift that needs to be taken into account.
Want to know a little more about who wrote this article? 👇
She has experience at Google, Meta and TikTok, where she led business, product and digital strategy initiatives. She is currently the founder of Gogotechy, an investor in tech start-ups and a lecturer at IE Business School, helping to foster talent, entrepreneurship and innovation within the tech ecosystem.
‘If you’re curious about this space, you know where to find us: info@gogotechy.com’