Enterprise Solutions Engineer

Datalab•New York, NY
•Remote

About The Position

Datalab is an applied research lab in New York that trains its own models to transform documents into verifiable data, including scans, dense tables, and handwriting. Because Datalab owns its models, customer challenges directly inform the product roadmap. Their open-source contributions (Marker, Surya, Chandra) have garnered over 70,000 GitHub stars. Notable customers include Anthropic, ElevenLabs, Gamma, Reflection AI, and Legora, as well as various insurers, financial firms, and healthcare companies. Datalab offers flexible deployment options, from API to fully air-gapped on-premise solutions. As a small, founder-led team, this role offers significant influence over sales strategies and product development.

Requirements

  • Significantly contributed to closing large (six-figure) opportunities, with concrete examples.
  • Credibility with engineers: ability to read API docs, write scripts, debug deployments, and converse with ML engineers and CISOs.
  • Presence with executives: ability to engage with C-suite buyers and make the business case.
  • Understanding of enterprise deal progression, including multiple stakeholders, security reviews, procurement, and budget cycles.
  • Comfort working in an early-stage environment without a defined playbook.
  • A drive to own the outcome rather than hand it off.

Nice To Haves

  • Experience with Document AI, OCR, parsing, extraction, or LLM evaluations.
  • Enterprise sales experience in financial services or insurance, or with AI-native companies.
  • Experience with on-prem or regulated deployments.

Responsibilities

  • Own opportunities from the first conversation to the signature.
  • Win the technical evaluation, including scoping the problem, running proof of concepts, and designing deployments (API, VPC, or on-prem).
  • Make the business case to customer leadership, not just engineers.
  • Own pricing and commercial terms.
  • Bring learnings back to product and engineering teams, influencing product development.
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