Founding GTM

Datalab trains models that read documents reliably at scale. The worlds most important information is trapped in PDFs scans and files that cant 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.

Were 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 70000 GitHub stars and broad developer mindshare. Were backed by founding members of OpenAI FAIR and Hugging Face.

Were 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. Were 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 wont 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 isnt fully defined. Youll 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 isnt 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. Theres a clear path to sales leadership for the person who builds the function well.

• 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 - youre 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.

• Running the inbound deal cycle independently for most enterprise accounts.

• Cycle time on inbound deals shorter than todays baseline.

• Outbound experiments live with first self-sourced pipeline starting to land.

• 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.

You think of yourself as a builder who happens to be in sales. Youre energized by the fact that nothing is fully figured out yet and youd rather invent the system than inherit one. You take satisfaction in process - clean CRM hygiene weekly metrics reviews postmortems on lost deals.

Youre 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 youre at the edge of your depth and need to bring in an engineer.

Youre 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.

Youre collaborative. You make the call thats 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.

• 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 didnt 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.

• 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.

1. 30-minute intro call with the founder.

2. Sales process deep-dive - walk us through a complex deal youve owned end-to-end.

3. Mock discovery demo using our product with discussion of a 1-page outbound strategy youll submit beforehand (well provide the brief).

4. 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.

Datalab is an equal opportunity employer. We do not discriminate on the basis of any characteristic protected by federal state or local law.

If you need an accommodation to participate in our hiring process or if you believe you have experienced discrimination or harassment at any point in it contact