Hiring GTM Leaders Is Broken Right Now
The way we sell, market, and run revenue is being rebuilt around AI agents. Most hiring processes have not caught up.
Most GTM resumes look the same on paper
Quotas hit, regions managed, segments grown. None of it tells you whether someone can sell, build, or lead in an AI-native sales motion.
Your network is tapped out
The same 30 candidates are circling the same 30 jobs. Top operators are not on the open market — they're 1–2 introductions away from someone who knows them well.
Recruiters don't know what good looks like
Most recruiting partners have never carried a number, run a board review, or shipped an AI agent into production. They optimize for placements, not for fit.
AI is rewriting the GTM playbook
Pipeline math, attribution, RevOps tooling, SDR motions, and forecasting are all being rebuilt. The leaders you hire today need to thrive in that shift, not resist it.
Roles We Place
Senior, AI-fluent operators across the full go-to-market motion.
Chief Revenue Officer
Operators who can scale a number from $5M to $50M+ ARR with an AI-augmented sales org.
VP Sales / VP Sales Engineering
Hands-on leaders who hire, coach, and deploy AI agents into the sales workflow without slowing close rates.
VP / Director of Marketing
Demand-gen and product-marketing leaders fluent in agentic ABM, lifecycle automation, and AI-driven content systems.
VP / Head of RevOps
Builders who own the data layer, tooling stack, and metrics that AI agents depend on — from CRM hygiene to forecasting.
SDR / BDR Leadership
Front-line managers who can run a hybrid human + AI prospecting motion and actually move pipeline, not just activity.
Customer Success / Post-Sales Leadership
CS leaders who can deploy AI agents into onboarding, support, and expansion — and own NRR as a number, not a vibe.
What "AI-Savvy" Actually Means
Every candidate today claims to "use AI." We screen for what actually matters.
Has shipped, not just sat through demos
Used Clay, Cursor, Claude, ChatGPT, n8n, Zapier, or custom agents in their day-to-day GTM workflow — and can show you the workflow.
Thinks in systems, not seats
Asks how leads are scored, how data flows, where the agent makes the call vs. the human. Treats GTM as a product.
Comfortable being wrong out loud
Iterates on prompts, playbooks, and ICPs the way good engineers iterate on code. Ships v1 instead of debating v3.
Reads the model release notes
Knows the difference between an Opus and a Haiku, an MCP server and a function call, a fine-tune and a RAG. Not because it's trendy — because it changes the plan.
How We Run a Search
Calibration call
30 minutes. We pressure-test the role, the comp, the stage, the team gaps, and what 'good' looks like 12 months from now. If it's the wrong search, we tell you.
Shortlist in 10–14 days
3–5 operators we'd hire ourselves. Each one comes with a written case for fit and a candid note on the trade-off you're making. No resume dumps.
Hands-on through close
We sit on the loop, calibrate after every interview, broker offers, and stay involved through the first 90 days. You get an operator's read, not a recruiter's update.
Why Companies Hire PipeIQ Talent
20+ years as a Bay Area GTM operator
Built and led GTM teams across early-stage startups and enterprise software. Carried the number. Sat in the QBR. Hired and unhired.
Operator network, not a database
Top candidates come from people who've worked with them. Our shortlists start with founders, ex-managers, and customers — not LinkedIn filters.
Built on top of an AI-agent company
PipeIQ deploys AI agents for sales, marketing, and RevOps every day. We know what AI-savvy looks like in practice because we ship it.
Aligned on outcomes, not headcount
We win when the hire is still in the seat and crushing the number 12 months in. Engagement structure reflects that.
Have a GTM seat to fill?
Tell us the role, the stage, and what you've already tried. If we're a fit, you'll have a shortlist in two weeks. If we're not, we'll point you to someone who is.
PipeIQ Talent is a service line of PipeIQ.
