GTM AI Engineer

Function:
RevOps / Founder's Office
Reports to:
CEO
Type:
Full-time
Compensation:
$160–200k base + meaningful equity
Why this role exists
Suppli is going after a generational opportunity: becoming the AI-native AR and credit operating layer for the physical economy. Every manufacturer, distributor, wholesaler, and dealer that moves physical goods on trade credit. That's a multi-trillion-dollar working capital system still being run on 30-year-old ERPs, homegrown spreadsheets, and small, overlooked credit teams. No company has established itself as the category leader yet. That window is open right now and it will not stay open forever.
The product side of that equation is already working at a level most Series A/B companies never see:

• ~$70k ACV today, clear line of sight to $100k+ with new modules already rolling out
• ~90-day average sales cycle - fast for a system-adjacent platform
• ~35% close rate from Stage 2 to closed-won
• One customer churn in the history of the company
• Net Dollar Retention well north of 120%, with a meaningful number of customers more than doubling ACV between month 12 and 24
• $6B+ in open AR flowing through the platform, producing a compounding data advantage that deepens with every account
• Proven outcomes: 15% avg DSO reduction, 16% avg past-due AR reduction, 90-day time to value

The macro tailwinds are landing at the same time. In a recent CFO survey, 79% already have AI in production or piloting, 57% are under moderate-to-strong board pressure to move on AI, 92% are willing to shift labor budget to AI tools, and AR automation is the 3rd-highest AI investment priority in finance. We don't need to convince CFOs AI matters. We need to get in front of more of them, faster.
With economics like these and a market this ready, the growth equation is simple:
how many of the right conversations can we create per rep, per week.
That's the bottleneck today.
Suppli runs an entirely outbound, phone-led motion with five full-cycle AEs who do everything from prospecting, research, list-building, enrichment, sequence writing, enrollment, discovery, and close. That's three jobs jammed into one. Every minute a rep spends researching on LinkedIn or manually enrolling a contact is a minute off the phone, and in our motion the phone is where deals happen.
Instead of hiring five BDRs to support five AEs, we want to give each AE the leverage of a 5–10 person team through AI, automation, and systems that learn. If we can get reps as close to 100% selling time as possible, the math stops being theoretical and starts compounding quarter over quarter.
This role holds the keys to making that real. It's not a traditional RevOps seat keeping the trains on time. It is the single highest-leverage hire we can make to convert a working product, a massive TAM, and an AI-ready buyer into the multi-billion-dollar outcome we believe is there.
Mission
Build and operate the AI-powered systems that ensure every Suppli rep spends ~100% of their time talking to the right prospects, at the right time.
Every system you build, tool you evaluate, and workflow you automate gets measured against one north star: rep selling time against the right-fit accounts.
The bar: AI obsession
GTM engineering is overplayed. Someone who spins up a Clay instance, connects ZoomInfo, and calls it AI automation is already obsolete. That's not this role.
We're looking for someone who treats AI as an arms race and can't stop themselves from staying ahead of it. Not because the job requires it, but because using last month's model when a better one shipped last week is physically uncomfortable to them.
What That Looks Like In Practice

• Follows the frontier, not the press releases. Knows what shipped last week across Anthropic, OpenAI, Google DeepMind, etc. from model cards and primary sources, not TechCrunch.
• Has a model selection framework. Real opinions about reasoning vs. classification vs. cheap high-volume vs. structured extraction, grounded in testing, not vibes.
• Builds when tools fall short. Off-the-shelf is the starting point. When vendor output isn't good enough, they build around it with Python, APIs, custom prompts, and eval loops.
• Has a portfolio of things they built for themselves. Weekend automations, personal tools, projects nobody asked for.
• Thinks in systems, not tasks. Asks about feedback loops, failure modes at 10x scale, and what gets better automatically over time.

In the interview we'll ask you to walk us through something you built with AI from first principles. What models you considered, what didn't work, what you'd do differently given what shipped in the last 90 days. The right candidate will give answers that make us feel behind.
What you'll own
Phase 1 — Sales automation (months 0–12)

• ICP & account intelligence. Build and continuously refine a dynamic, AI-enriched ICP model from closed-won and closed-lost data. Our ICP is tightly defined as physical economy businesses, $30M to low billions in revenue, with strong pull from next-gen ownership, PE-backed portcos, and companies at breaking points. Your output: a living, prioritized account universe reps never have to build themselves.
• Signal detection. Source and operationalize the buying signals our ICP telegraphs - things like PE ownership changes, new CFO or second-generation family leadership, ERP upgrades, M&A activity, AR/finance hiring surges, existing tech stack, growth inflection points. Automated scoring surfaces the highest-priority accounts to reps every morning without them asking.
• Enrichment pipeline. Every prospect record auto-populated with what a rep needs before their first call - financials, ERP stack, org chart, key contacts, PE ownership, recent news, credit team size. Zero manual research. HubSpot should be the only place a rep looks.
• Outreach automation. Automate contact identification, sequence selection, and enrollment across ZoomInfo, HubSpot, Nooks, and TitanX. The machine feeds the rep, not the other way around.
• HubSpot as source of truth. Own the CRM as a system: hygiene, workflows, reporting, integrations. If a rep does something manually that a system could do, that's a bug.
• Training and enablement. Instant cold call, intro call, and demo meeting scoring and coaching points. Giving reps a scalable way to create personalized product and feature content for prospects on the fly.

Phase 2 — Expansion (12 months+)
Once the sales machine is mature, this role expands into the same thinking across customer success, finance, and broader operations. You'll have significant input into what comes next.
First 90 days
No 30-day ramp. Week one should look like week five.

• Days 1–14. Embed with sales. Shadow every rep. Map every manual step in the current prospecting, enrichment, and enrollment workflow. Audit the stack - HubSpot, ZoomInfo, Nooks, TitanX. Deliver a written prioritization memo to our CEO identifying the three highest-leverage fixes.
• Days 15–45. Ship the first automation against the highest-friction item. Reps should feel the difference before day 45. Start building the ICP scoring model from our closed-won and closed-lost data.
• Days 46–90. Enrichment pipeline is live and every new prospect auto-enriched without rep input. Signal detection is running. Reps can articulate a clear before/after in how they spend their day.

Requirements
Tech stack experience

• HubSpot (workflows, reporting, data model)
• ZoomInfo, Titan X for prospecting data
• Python or JavaScript - scripts, APIs, custom pipelines
• LLM integration: calling APIs, writing evals, selecting models by task
• Prompt engineering beyond basic usage and orchestration layer (Claude, n8n, etc.)

AI Obsession Requirements

• Tracks model releases as they happen, not after
• Has a real framework for model selection by task
• Has built custom AI pipelines, not just configured SaaS
• Can articulate tradeoffs between frontier models today
• Portfolio of personal AI projects that weren't assigned

Not Required

• Traditional software engineering background
• Enterprise SaaS experience
• AR, credit, or finance industry knowledge
• Formal CS or engineering degree

You'll thrive here if you...

• Have built something from scratch with AI and can explain every decision you made
• Track model releases the way some people track sports scores
• Treat off-the-shelf tools as a floor, not a ceiling
• Get viscerally frustrated by manual work a well-prompted model could handle
• Measure yourself by what you shipped, not what you worked on
• Prefer creating structure to waiting for it
• Want to be a builder on a rocket ship, not a manager on a ladder

This is the wrong role if you...

• Think GTM engineering means being good at Clay
• Follow the AI space casually and use whatever model is default
• Need detailed specs before starting
• Measure progress in tools evaluated instead of things deployed
• Want to stay in a lane

How we work
Suppli's culture is intense, empathetic, high stakes, and genuinely fun. We move with velocity because the opportunity to build a multi-billion dollar company is up for grabs. But velocity without direction is just chaos, so every fast decision is anchored to impact. We're direct and rigorous in how we evaluate the business and give feedback, and we do it with real care for the people on the other side of the conversation. We hire people who treat their work as a craft, ship things that make the company incrementally better every day, and hold themselves to outcomes, not just effort.
Compensation

• Base: $160k – $200k
• Equity: Meaningful - every team member is an owner.
• Structure: Reporting to directly to our CEO, Ryan Ayers.

Growth path

• 0–12 months. Own the sales automation infrastructure. Become the operational backbone of the sales team and establish how AI gets deployed internally at Suppli.
• 12–24 months. Expand into customer success and finance operations. Shape Suppli's internal AI strategy - which functions get automated next, how tooling decisions get made, what the stack should look like at scale.
• 24 months+. For the right person, this becomes Head of AI & Automation. You own (and obsess over) our revenue / headcount multiple. That role doesn't exist yet. The right hire builds it into existence.