What 2,600+ Open Cybersecurity GTM Roles Actually Say About This Market

Most hiring commentary in this industry runs on vibes: a few LinkedIn posts, a handful of anecdotes from people currently searching, and a general sense that the market is either brutal or booming depending on who's talking. I wanted an actual answer, so I built the GTM Hiring Landscape, a live, nightly-refreshed dashboard built on top of the same crawler infrastructure behind GTM Radar, pulling from public applicant tracking feeds across 11 platforms as well as direct crawls of individual companies' own careers pages where no public ATS feed exists. As of the live dashboard's most recent refresh, that's 2,615 open roles across 234 actively hiring companies, out of 458 pre-IPO cybersecurity companies tracked, a 0.26 to 1 BDR/SDR-to-AE ratio, 48 percent of roles listed remote, and a 22-day median time posted. This dataset refreshes nightly, so treat every number in this post as accurate at the moment of publishing rather than a fixed figure. The current live numbers are always on the dashboard itself.

Worth naming why the source list looks the way it does: LinkedIn, Glassdoor, and Indeed aren't in it, and that's not an oversight. None of the three expose a public feed of open roles, and all three actively block the kind of systematic crawling this dataset depends on. What they show a given user is also personalized and incomplete in ways that aren't disclosed, which makes them fine for a single job search and useless as a source for an actual dataset. Going straight to the ATS feeds and careers pages companies use to actually manage their hiring, rather than the aggregators that repost a subset of it, is what makes every number here a direct count instead of a scrape of whatever an algorithm decided to surface.

One more methodology note, since it's new as of this update: the crawler's discovery step, the part that finds new companies to add to the tracked set in the first place, now includes a genuinely agentic layer, not just a bigger regex. The original discovery pipeline matched headlines against two fixed sentence patterns ("X raises funding," "X emerges from stealth"), which meant it was structurally blind to anything phrased differently: an acquisition, an executive hire, a departure, an expansion. I added a second pass that hands the headlines that pattern rejects to Claude, with no fixed template to match against, and lets it judge each one independently: is this a real signal, what kind, how confident, what's the actual company name. In its first production runs this surfaced signal types, acquisitions specifically, that the fixed-pattern version could never have produced regardless of how long it ran, because no pattern for that category ever existed in it. That's the actual distinction between systematic and agentic in practice, not a branding choice: a system executing rules it was given versus a system judging cases it wasn't explicitly programmed to handle.

One scope note up front, because it matters for how far to extend any of this: every company and role in this dataset is pre-IPO and specifically cybersecurity. I don't track public companies, and I don't track other verticals. That's a deliberate boundary, not a gap in the crawler, this is the market I actually operate in and know well enough to interpret correctly, and I'd rather report a smaller dataset accurately than a broader one I can't vouch for. None of what follows should be read as a statement about GTM hiring in SaaS broadly, in public cybersecurity companies, or in any market outside this specific slice.

A second note, since the first has a way of getting lost: every number in this post is accurate as of the moment it was published. The underlying dataset refreshes nightly, which means the topline figures will have moved by the time you're reading this, usually by a small amount, sometimes not. If you want the number as of right now rather than as of publication, the live dashboard is always current. The patterns discussed here, the leadership gap, the pipeline-to-closing ratio, are the durable part. The exact figures are a snapshot.

Nothing in the dataset itself is modeled, sampled, or estimated. It's a direct count of what's actually posted, right now, within that pre-IPO cybersecurity scope, and two findings in it are worth pulling out on their own: how scarce leadership-level hiring actually is, and what the ratio of closing roles to pipeline-generation roles says about where this market is headed.

The leadership gap is bigger than it looks from inside a job search

Across all open roles at the time of publishing, the seniority breakdown is stark: 4 at C-level, 1 SVP, 21 VP, and 25 Head of, 51 roles total at VP level or above, against 1,564 individual contributor roles and another 746 at manager or lead level. Leadership-level openings make up roughly two percent of everything currently posted, across pre-IPO cybersecurity specifically. I'd expect the shape of that scarcity to hold directionally in adjacent markets, but I haven't tracked them, so I'm not claiming it does.

That number matters more than it might seem to on first read, because it changes what a leadership-level job search should actually look like. If you're searching for a VP or C-level GTM role, the posted market isn't a representative sample of the real market, it's a fraction of it. Most senior seats at this level get filled through networks, warm introductions, and executive search before they're ever listed publicly, which means treating job boards as your primary search channel at this level is treating the smallest, least representative slice of the market as if it were the whole thing. The practical implication isn't that leadership roles don't exist. It's that finding them requires a fundamentally different motion than scrolling postings, more relationship-driven, more proactive, and far less dependent on whatever happens to be live on a careers page this week.

This is also where it helps to actually look rather than rely on the aggregate stat. Filtering GTM Radar to marketing at the VP, Head, and C-level bands shows you the sparse, real list behind that two percent figure, not just the number. It's a short list, and that's the point: at this level, scanning what's actually posted takes minutes, not hours, which makes it worth doing directly rather than trusting a summary statistic secondhand. Separately, my crawler also scores companies on signals like recent funding, hiring velocity, and role mix, the kind of thing that tends to precede a leadership hire before a req is ever posted, but I'm not treating that as a public, filterable view here since I haven't built or confirmed a clean way to surface it as its own tool yet. Watching the funding and expansion signals in the underlying dataset is still the more proactive move for a leadership-level search than waiting for a posting to appear, it's just not a single link I can hand you today.

This is exactly the gap I built the GTM Hiring Scope Builder to address from the other direction: if the posted leadership market is this thin, the leadership roles that do exist need to be scoped with real precision, because a company that gets a rare VP or CMO search wrong doesn't get many chances to run it again quickly.

The BDR/SDR to AE ratio says more about the next two quarters than the current one

The second number worth sitting with is the ratio between pipeline-generation roles and closing roles. There are 162 open BDR and SDR roles against 632 open Account Executive and Sales IC roles, a ratio of roughly 0.27 to 1 at the time of publishing. Put plainly, this market is hiring roughly one dedicated outbound pipeline-generation role for every four closing roles.

That framing undersells the real picture if BDR/SDR is treated as the only pipeline-generating function, though, because it isn't. Demand Generation and Growth accounts for another 73 open roles, and Field and Partner Marketing adds 85 more, both of which exist specifically to produce qualified pipeline, just through inbound, campaign, and event-driven motions rather than outbound dialing and sequencing. Counted together, BDR/SDR, Demand Gen, and Field Marketing add up to 320 open roles against 632 AE roles, a ratio closer to 0.51 to 1, roughly one pipeline-generating role for every two closing roles. That's a meaningfully less alarming picture than 0.27 to 1, and it's the more accurate one, because pipeline in this industry has never come from BDRs alone.

It's also worth naming the dynamic this data quietly complicates. The standing complaint from sales, in nearly every GTM org, is that marketing is perpetually behind on sending over qualified leads. That complaint is old enough to be a cliché, and it shows up regardless of how the underlying hiring is actually structured. What this data suggests is that even the broader, more generous count of pipeline-generating roles, 320 against 632 closers, still puts pipeline generation meaningfully behind closing capacity. If a company's answer to "marketing isn't sending enough qualified pipeline" is to hire fewer demand gen and field marketing roles, or to leave that function thin while continuing to staff up AEs, the ratio only gets worse, and the complaint doesn't go away, it just has less capacity behind it to eventually resolve. A lapse in the marketing function isn't a fix for slow pipeline. It's very often the reason for it.

If you're a company reading your own hiring plan against this benchmark, the question worth asking honestly is where your pipeline is actually going to come from if your combined BDR/SDR-plus-demand-gen-plus-field-marketing headcount looks thin relative to your AE headcount. My Pipeline Coverage Calculator runs exactly this kind of math, working backward from a revenue target through win rate to the pipeline volume required, segmented by source, so you can see concretely whether your current pipeline-generation hiring, across sales and marketing both, actually supports the closing capacity you're building alongside it.

Where the rest of the data adds useful texture

A few other patterns in the dataset are worth knowing, even though they're not the headline.

Funding stage changes what a company hires for, not just how much. Marketing's share of open roles peaks at Series A and Series C, the two points where a company is most often repositioning rather than simply scaling what already works. Dedicated Revenue Operations roles barely register before Series B and roughly double afterward, which tracks with the point where a company stops running on founder energy and starts needing an actual system underneath the sales motion. Customer success runs heaviest at PE-backed companies, where retention is frequently the entire thesis of the deal.

The remote data has a trap in it. Marketing looks like the least remote function in go-to-market overall, 35 percent, against 51 percent for sales. But that gap is almost entirely explained by Community and DevRel, which sits inside the marketing function at only 4 percent remote and pulls the whole category down. Strip that one sub-function out and marketing's remote rate tracks the rest of go-to-market closely. Worth knowing if you're reading the category average as your own odds in a marketing-specific search.

Posting velocity needs to be read as time-to-fill, not demand. The trailing 12-week chart on the landscape page shows a sharp rise in postings, but that's a survivorship artifact, filled or expired roles have already dropped off the boards they came from, so older weeks are structurally undercounted. Of the currently open roles, 377 were posted more than 90 days ago against 1,439 in the last 30. That's what a snapshot of still-open roles looks like, not evidence of a hiring surge. A real week-over-week demand series needs historical snapshots compared against each other over time, which is exactly what accumulates in the background for this dataset and will eventually replace that chart once there's enough history to mean something.

Salary band width is itself a signal. A wide base salary band on a given title usually means the title covers genuinely different jobs at different companies, and that's exactly where a candidate gets underpaid by negotiating against the title instead of the actual scope. Before you're on either side of that conversation, it's worth checking how roles get confused with each other so you're negotiating against the real job, not the label on it.

Req count alone doesn't tell you what you think it tells you. A company with a large number of open roles could be aggressively funded and moving fast, or it could be failing to close the reqs it already has open. The landscape page pairs req count with median days posted for exactly this reason: a company opening dozens of roles with a six-day median age is actively building. A company sitting on a similar number of roles with a 90-day median age has a band, a process, or a scoping problem, and as a candidate, that's often where an application is most likely to go unread, and also where you have the most real leverage if you're genuinely a fit.

Use the actual data instead of the anecdote

Every number in this post is pulled directly from the GTM Hiring Landscape, which updates nightly and exports to CSV from every panel. If you want to see the actual roles behind any of these numbers, filterable by function, seniority, region, and investor, that's what GTM Radar is built for, and the daily digest will surface new roles matching your filters every morning without you having to check back manually.

If you're on the hiring side and this data has you rethinking whether a role is scoped realistically against what the market is actually paying and actually staffing for, that's exactly what the GTM Hiring Scope Builder and my GTM Alignment Diagnostic are built to work through before the job description goes live, not after it's been open for 90 days.