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Founding NYC Account Executive

🏢 Encord · 📍 New York · 💼 onsite · ⏰ FullTime
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Position Summary & Responsibilities

About us

Encord is the universal data layer for AI that helps 300+ AI teams train and run models on the right data. Our platform indexes, curates, annotates, and evaluates data across the full AI lifecycle, from development through production.

 

Trusted by Woven by Toyota, AXA, UiPath, Zipline, and more. We're an ambitious team of 100+ working at the frontier of AI and have raised $60M in Series C funding from Wellington Management, CRV, Next47 and Y Combinator.

 

The role

Encord is scaling rapidly, with strong product-market fit and a clear mandate to plant our flag in New York City. This is our first dedicated hire in the market — and the person who takes this role will be the founding presence that shapes how we show up on the East Coast.

You’ll be handed a genuinely compelling product with proven traction, a strong brand in AI circles, and the backing of a world-class team — then trusted to build from there. That means opening doors, winning deals, and laying the foundation for a team and office that grows around you.

Reporting directly to the Head of Sales and working closely with our founders, you'll take a category-defining AI infrastructure platform to market — selling into the most advanced AI teams in the world as we expand from core computer vision into Physical AI, one of the next major frontiers in AI.

This is a rare opportunity: traction is proven, the product is real, but the New York chapter hasn't been written yet. You'd be the one to write it.

What you’ll do

  • Own the full sales cycle end-to-end, from pipeline generation through close

  • Be Encord's first on-the-ground presence in New York — build our brand, network, and pipeline in the market from day one

  • Sell into sophisticated mid-market and enterprise teams building frontier A

🎯 Candidate Preparation Guide For Encord Applicants

Key Role Competencies & Evaluation Highlights

Key Role Focus:

Evaluating full-stack engineering excellence, scalable data labeling and curation infrastructure, and the capability to handle massive multi-modal AI datasets.

📋 Preparation Priorities (Key Areas to Clarify):
  • 1. Treating data tooling as simple CRUD applications rather than performance-critical scientific workflows.
  • 2. Ignoring frontend performance bottlenecks when rendering large multi-modal datasets in the browser.
  • 3. Failure to grasp the iterative feedback loop between data quality and model performance.
✨ Recommended Role Alignment Hook:

I build high-performance data infrastructure that streamlines the most painful bottleneck in AI development: turning raw multi-modal data into clean, annotated gold.

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