Embedded engineers · example profiles
Embed a GTM engineer inside your team.
Hire embedded, full-time GTM engineers who join your Slack or Teams and work your backlog from week one. The building is the hard part. This is the bench that builds, with my architecture and weekly oversight on top.
Companies where we've embedded GTM engineers
Official partners
Certifications on the bench
Engagement terms
What you get when you engage.
Every engineer is vetted for production-grade delivery before they touch your roadmap.
I architect and oversee weekly. Each engineer runs 2 to 3 POCs in parallel.
Placement runs through AYTalent. The engineers are employed and backed by its bench, not freelance one-offs.
Everything that’s included
The engineer ships on our Claude Code subscription. You never see an AI tool bill from this engagement.
One dedicated channel. Async by default, synced when needed. No tickets, no agency portal between you and the work.
A secure setup where everyone uses every agent while the core API keys stay locked away. Built in from the start.
The engineer works on a separate environment. Nothing hits your live systems without your sign-off.
Short end-of-day update when something meaningful ships. No black box, no surprise changes.
If the person is wrong, we swap them with a full handover through the shared channel. No restart cost.
What a GTM engineer actually is
A GTM engineer builds and owns the systems that go-to-market runs on. Enrichment, routing, scoring, sequencing and the logic that decides what happens when a signal arrives. The output is working software inside the revenue stack, not a document describing one. The enrichment half of that usually runs in Clay and what the work actually consists of hour by hour is written up on its own. If the question is how to get one rather than what one does, the three routes to the capacity are set out separately.
The most-quoted number about the role is 54% and it is usually quoted without its population. It comes from a research report published by The Signal on 23 April 2026, which found that “Once I looked at the actual work instead of the label, 34 of 63 companies have someone doing GTM Engineering today.”
So the base is 63 fast-growing SaaS companies one analyst tracks and the count is of the work rather than the job title. Filtering those same 63 on the title gives a much smaller number: “When I filtered on the literal ‘GTM Engineer’ title, only 10 companies showed up.”
Private B2B SaaS as a whole is a different and much larger population and there the same report puts it at “only between 3-7% of private B2B SaaS companies have at least one GTM Engineer on staff”, with the lower bound applying to the literal job title and the upper bound reached only by counting adjacent Growth Engineer and GTM-scoped RevOps Engineer roles.
That gap is the practical point. If you are hiring for this seat you are competing against a small number of companies for the title and a much larger number for the skill and most of the people who can already do the work are not carrying the label yet.
Your first 30 days
Requirement analysis, 1 to 2 days. What you want built decides who you meet.
Three anonymized profiles from a 30+ bench, one flagged as my recommendation. Your pick.
You talk to your engineer before anything starts. Wrong fit? You meet the next one.
Inside your Slack or Teams and your tools, shipping in week one. Money-back month 1, 90-day replacement.
The bench · six example profiles
What the profiles look like.
Each one shows the superpower, the shipped work with employers removed, the relevant experience and the stack. Real profiles arrive in this exact format, matched to what you want built.
Lead scoring and signal engines, end to end. Six years across data, backend and the AI layer. Turns first, second and third-party signals into a score a rep actually trusts, with the reason for the score attached so adoption sticks. The one you point at your hardest revenue-signal problem.
- Account-scoring engine for a B2B marketplace. 78k contacts scored nightly, ranked rep lists, next best move drafted per account.
- Explanation-of-score layer. Every lead shows why it scored, the piece that got the sales team to actually trust it.
- Visitor-detection + hand-raiser engine for an ABM agency. Warm inbound went from a trickle to roughly 20 a month.
- CRM cleanup pipeline. Dedupe, owner rules, stage hygiene across 250k records, human-approved merges.
Builds scoring and signal engines inside client GTM teams, ships to production weekly.
Owned the nightly scoring pipeline across 78k contacts, from ingestion to the rep-facing app.
Full-stack, product-grade. Seven years shipping the apps and dashboards a GTM team lives in. Builds the rep-facing surface, the secure auth underneath and the mission-control view on top, so the whole team sees the same numbers refreshed nightly.
- Rep enablement app for a sales team of 40. Hot lists, score transparency, per-lead feedback loop, OAuth on the company domain.
- Mission-control dashboard for a marketplace GTM team. Pipeline, spend and engine health in one page, refreshed nightly.
- Client portal with end-to-end encrypted credential handling and a full audit trail.
- Secure multi-user layer. The whole team runs the agents while the core keys stay locked away from them.
Builds internal GTM tools and dashboards inside client teams, front to back.
Shipped the mission-control dashboard and the rep enablement app end to end.
Automation-first. Five years wiring systems that never spoke before into reliable, human-gated rails. Multichannel outreach, 200+ integrations, reactivation engines, every one with alerting and budget caps so nothing runs away unattended.
- Multichannel outreach rails. Email + LinkedIn + WhatsApp sequences with human send gates, wired through Instantly, Unipile and a WhatsApp Business rail.
- 200+ integrations across CRMs, ad platforms and data providers, monitored with alerting and budget caps.
- Reactivation engine on dormant accounts for an e-commerce platform. Drafted messages, human approved.
- Owner-rules + dedupe automation that keeps the CRM clean without a human babysitting it.
Builds outreach rails and integration engines inside client teams, human-gated.
Built the reactivation engine on dormant accounts, drafted and human-approved.
Second brains and retrieval. Four years turning scattered company knowledge into one queryable memory your team taps from their own tools over MCP. PII-masked, role-based, EU-hosted, every query logged. Currently placed, on the waitlist for the next opening.
- Company second brain for a marketplace. 40+ data sources into one queryable memory, MCP access for the client’s own team.
- Meeting-brief generator. CRM + calls + news compressed into one screen, 90 seconds to read.
- Data-privacy hardening. PII masking, role-based access, EU hosting, logged queries.
- Context layer wired into the client’s own Claude, so their team asks the brain from where they already work.
Builds company second brains and MCP retrieval layers inside client teams.
Built the company second brain across 40+ sources plus the privacy hardening.
SEO x GEO content factories. Six years building the machine that gets you found in search and in the AI answers. Programmatic pages behind a quality gate, plus a GEO tracker watching what the LLMs cite about your category, so you know where you show up and where you do not.
- Page factory with a quality gate for an accounting software company. Ranked on a new regulatory offer inside 7 days.
- GEO citation tracker. 120 buyer questions watched across ChatGPT, Perplexity and AI Overviews, gap reports weekly.
- Programmatic comparison pages that the LLMs now cite in category answers.
- Content ops with a human review gate. Volume without the sludge, every page checked before it ships.
Builds page factories and GEO trackers inside client marketing teams.
Built the page factory plus the GEO citation tracker across the category.
Paid-media engines. Five years closing the loop between revenue and the ad platforms. Feeds closed-won back as the bidding signal, runs a creative testing loop that compounds, wraps every budget move in guardrails so a bad night cannot drain the account.
- True-conversion feedback loop. Closed customers and revenue fed back to the ad platforms as the bidding signal.
- Creative testing loop. Brief, generate, test small, judge on buyers, learn. Every generation starts where the last finished.
- Spend guardrails. Caps, canaries and automatic rollbacks on every budget move.
- Cross-platform reporting. Google and Meta pulled into one view your team reads in a glance.
Builds bidding-signal loops and paid-media guardrails inside client growth teams.
Built the true-conversion feedback loop plus the spend guardrails.
What it costs and what happens if the fit is wrong.
The questions buyers ask on the scoping call, answered here instead. Every number below is either published in the strip at the top of this page or carries its source.
What does a GTM engineering agency cost?
5000€ - 6500€ per engineer per month to embed one from this bench, the figure in the strip above. Hiring your own is a different quantity. The median base salary for a US GTM engineer is $150,000, measured across 235 priced US roles in a May 2026 benchmark. That is base pay, before employer costs, equity, tooling and whatever the search itself costs you. Neither number converts into the other. A vendor quoting you one blended figure is not telling you which of the two it came from. The salary evidence, including the archetype split from $135,000 to $218,750 and the employer bands behind it, is on the GTM engineer explainer.
How fast can a GTM engineering agency start?
72 hours to embedded, shipping inside week one. That is the number in the strip above. It is the point of going through an agency: the engineer is already employed, already trained and already on the bench when you ask. A direct hire starts after your search, your offer and their notice period, whatever those come to at your company. Nobody can quote you that last number except you.
Should you hire, contract or embed?
Hire when the work is permanent, the budget carries a full salary and you can wait out a search. Contract a freelancer when the job has a defined end and you can supervise the build yourself. Embed when you need the work owned now and want someone else carrying the employment, the training and the replacement risk. Contract a freelancer for work that turns out to be permanent and the systems outlive the contract, with nobody left who understands them. The full decision, including what the search costs in time and how to judge a candidate, is in the buyer's guide to hiring a GTM engineer.
When is a company ready for its first GTM engineer?
When there is revenue systems work that nobody owns. The signal is a backlog, whatever the headcount or funding stage. Routing that breaks quietly, a CRM the reps have stopped trusting, scoring that sales ignores, tools bought faster than anyone wires them together. If that backlog currently sits with a RevOps generalist who does not code, or with a sales leader doing it after hours, the role already exists at your company and nobody is in it.
What if the engineer is not right for the job?
You talk to your engineer on a call before kickoff. If the fit is wrong you meet the next profile instead. After kickoff the first month is money-back and a 90-day replacement guarantee applies. Both terms are published in the strip above. They exist because matching is the step most likely to go wrong. Pricing the risk into the engagement is cheaper than arguing about it later.
What is the difference between a GTM engineering agency and a GTM strategy consultancy?
A GTM engineering agency ships the systems; a GTM strategy consultancy hands you the plan for them. The agency writes the code and owns the pipeline in production. It is still there when that pipeline breaks. A strategy consultancy delivers a document your team then has to staff and build from. Which one you want depends on whether the gap at your company is knowing what to do or having somebody to do it.
Is a GTM engineer the same as RevOps or a sales engineer?
No. A GTM engineer builds the revenue systems. RevOps owns the process and the reporting around them. A sales engineer works deals in front of customers. A forward deployed engineer is the fourth title in the same pile. The split there is whose building the work happens in: an FDE embeds with a customer to build their own employer's product, a GTM engineer builds inside your company for your own revenue team. The titles blur in job ads because the role is young and companies reuse whichever req their ATS already has. It is also why you have to pick the archetype before you write the budget: they sit $83,750 apart in base pay. The full comparison, with the org chart and where each seat reports, is on the GTM engineer explainer.
Want the three real profiles for your use case?
Tell me what you want built. You get three anonymized profiles matched to it, one recommended, then a call with your pick before anything starts. Terms are in the strip up top.
Book a scoping call →Placement runs through AYTalent. Engineers are employed, trained and backed by the bench, never freelance one-offs.
Want profiles by email first?
Tell me the job to be done. I reply with three matched profiles.