Founding Gtm in United States

About Datalab Datalab trains models that read documents reliably at scale. The world's most important information is trapped in PDFs, scans, and files that can't easily be parsed, and getting it out correctly matters. From frontier AI labs processing training data to Fortune 500s like Siemens extracting decades of engineering records, Datalab is where businesses turn to when extraction has to be right. We’re at an 8-figure run rate with a team of 7. Anthropic is a customer. And we have hundreds more across FAANG, frontier AI labs, healthcare, finance, government, and legal. Our tools, Chandra, Surya, Marker, and Lift, have 70,000+ GitHub stars and broad developer mindshare. We're backed by founding members of OpenAI, FAIR, and Hugging Face. Role Overview We're hiring our founding GTM - someone who can run the full cycle of sales; sourcing leads, managing the sales process, and closing deals, all while building the playbook that future hires will run on. Datalab makes document AI infrastructure that powers extraction at scale. We're at 8-figure revenue, and have grown revenue >5x YoY, with a team of 7. Anthropic uses Datalab. So do hundreds of other companies across FAANG, frontier AI labs, financial services, insurance, logistics, healthcare, and government. Our open-source projects (Marker, Surya, Chandra) have 60k+ stars and wide community adoption. Sales today is founder-led. The goal of this role is to build a real sales motion on top of that foundation - outbound, ICP definition, enterprise process, and the playbook itself. You won’t be selling alone - engineers and the founder are heavily involved in the sales process, and the whole company pitches in to unblock deals and support customers. This is a high-ownership, high-ambiguity role. We have standard pricing in some areas and open questions in others. We have strong signals about who our best customers are, but ICP isn't fully defined. You'll work alongside the founder and our GTM team to figure those things out by closing deals. If you want to inherit a polished playbook, this isn't the right role. If you want to build that playbook at a company with real product-market fit, a steady inbound pipeline, and serious enterprise customers, this is a great fit. There's a clear path to sales leadership for the person who builds the function well. Day to day you will: Run the inbound deal cycle at volume on enterprise opportunities - discovery, demos, technical evaluation, pricing, security review, procurement, and close. Own the customer through successful deployment - you're the primary point of contact through onboarding and go-live. After deployment, accounts move to team support for reactive issues; you retain expansion and renewal on accounts you closed. Prioritize ruthlessly for enterprise accounts. Disqualify smaller inbound back to the self-serve flow, so we can learn from it. Define our ICP through every closed-won and closed-lost, in close partnership with the founder and chief of staff. Navigate technical sales - know when to loop in engineering for a POC, when to bring in the founder, and how to drive procurement, legal, and public-sector vehicles like GSA/SEWP. Keep CRM clean - every deal, every stage, every next step, forecasts that reflect reality. Build the outbound motion as inbound capacity stabilizes - identify high-fit accounts, run sequences, measure conversion, and double down on what works. By month 3 this should be producing meaningful self-sourced pipeline. Build the playbook - discovery scripts, demo flows, objection libraries, competitive battle cards, pricing guidance, qualification criteria. Close the product feedback loop - track what customers are blocked on and which features would unblock deals, prioritize by revenue impact, and bring structured signal to product and engineering on a regular cadence. What success looks like By month 3 Running the inbound deal cycle independently for most enterprise accounts. Cycle time on inbound deals shorter than today's baseline. Outbound experiments live, with first self-sourced pipeline starting to land. By month 12 Hitting ramped quota. Outbound channel producing meaningful pipeline, with first self-sourced closes on the board. Playbook v1 documented, named-account list and outbound sequences in a state the next hire can inherit. Ideal candidate You think of yourself as a builder who happens to be in sales. You're energized by the fact that nothing is fully figured out yet, and you'd rather invent the system than inherit one. You take satisfaction in process - clean CRM hygiene, weekly metrics reviews, postmortems on lost deals. You're technical enough to hold your own. Our buyers are engineers, ML leads, and CTOs. You should be able to ramp fast on what Marker, Surya, and Chandra actually do, talk credibly about benchmarks and evals, and know when you're at the edge of your depth and need to bring in an engineer. You're hungry. You read your own call recordings. You ask the engineering team how the model handles a specific edge case the prospect raised. You come back to the next call with a sharper answer. You’re collaborative. You make the call that's right for the company and team, not just your commission - working a small-commission strategic logo because the case study compounds, pushing sub-fit inbound back to self-serve instead of grinding it for personal comp, flagging when the brand or engineering team did the heavy lifting on a deal. You trust that doing the right thing grows the pie for everyone - including yourself. We're eager to work with someone who has: 5+ years in B2B SaaS sales with meaningful time in mid-market or enterprise. Owned complex, multi-stakeholder deals end-to-end - technical evaluation, security review, legal, procurement. Built outbound from scratch or rebuilt a broken motion, with clear metrics on what worked. Sold a technical product (APIs, infra, ML/AI tooling, developer platforms) to technical buyers. Operated in early-stage environments where the playbook didn't exist yet. Track record of meticulous CRM hygiene and rigorous pipeline math. Can use AI tools like Claude and Cowork effectively to streamline your work and build playbooks. Bonus points if you: Have sold document AI, OCR, IDP, or data extraction. Have closed deals in regulated verticals and are familiar with SOC 2, HIPAA, FedRAMP, DPAs, BAAs. Have sold both API/usage-based products and on-prem deployments. Have a technical background (CS degree, engineering experience, or strong self-taught fluency). Actively use open-source LLMs and/or projects. Interview process 30-minute intro call with the founder. Sales process deep-dive - walk us through a complex deal you've owned end-to-end. Mock discovery + demo using our product, with discussion of a 1-page outbound strategy you'll submit beforehand (we'll provide the brief). Onsite half-day in NYC with the team. At this stage of the company, every interview is somewhat custom, so these phases may be rearranged slightly.