Founding Account Executive, Encord
NYC
$225-325k
+ Equity & Commission
4+ days a week in office
Data platform for AI training
Open for applications
Data platform for AI training
101-200 employees
Open for applications
$225-325k
+ Equity & Commission
4+ days a week in office
101-200 employees
Company mission
To solve AI alignment by tackling the real bottleneck: data quality.
Role
Who you are
- Excited by the idea of building something — not just hitting a number, but opening a market
- Highly ambitious, competitive, and motivated by outsized ownership and impact
- Entrepreneurial mindset — you move fast, figure things out, and don't wait to be told what to do
- Strong commercial intuition and the ability to earn trust with senior technical and business stakeholders
- Comfortable selling complex, technical products (or excited to ramp quickly in a deep technical domain)
- Hungry to grow into a leadership role as the NYC team scales around you
- A history of strong performance in high-expectation environments — start-up experience a strong plus
- 4+ years of closing experience in B2B SaaS or technology sales, with a track record of meeting or exceeding quota
- Experience managing complex, multi-stakeholder sales cycles with deal values of $50K+
- Demonstrated ability to sell to technical buyers — including engineers, ML practitioners, or data scientists — and navigate to economic decision-makers
- Proven ability to self-source pipeline and drive deals from first contact through close
- Experience at a high-growth start-up or fast-paced sales environment preferred
- Familiarity with CRM tools (e.g. Salesforce, HubSpot) and structured sales methodologies (e.g. MEDDIC, SPICED, Challenger)
- Bachelor's degree or equivalent practical experience
- Bonus: Experience selling developer tools, infrastructure, or technical platforms. Exposure to mid-market or enterprise sales cycles. Start-up experience in fast-growth, execution-heavy environments. Curiosity about AI, robotics, or the future of Physical AI
What the job involves
- 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
- 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 AI products
- Drive high-impact deals and help scale Encord through its next phase of growth
- Work with customers solving real, complex problems across multimodal data, robotics, and physical systems
- Partner closely with Product, Engineering, and Customer Success to feed customer insight directly into the roadmap
- Shape the playbook — help define how we sell, who we target, and how we win in this market
- Lay the foundation for a NYC team
Our take
It has become increasingly clear that the next generation of AI applications will be driven by data-centric approaches concentrated around training data creation, management, and evaluation. Crucial within this process is the annotation or 'labelling' of data. Traditionally, such annotation has been left to human workers, which has historically made this part of the process of AI development expensive, slow, and difficult to scale.
Encord offers a computer vision annotation platform that automates a number of manual labelling tasks. Its suite of tools is designed for collaboration across roles and teams, from domain-expert annotators to project managers and machine learning engineers. This allows companies to iterate 10x faster, and develop and deploy high performing models in less time whilst saving on annotation costs.
Demand is clearly there: since its launch in 2020, Encord has facilitated the annotation of more than 100 million frames and images and served customers in verticals such as medical imaging, smart cities, sports analytics and satellite imaging. Furthermore, usage is scaling rapidly, with the number of labels generated on the platform growing ~70% month-over-month.
Steph
Company Specialist at Welcome to the Jungle
Insights
Company
Funding (last 2 of 5 rounds)
Feb 2026
$60m
SERIES C
Aug 2024
$30m
SERIES B
Total funding: $107.2m
Company benefits
- Competitive salary, commission, and meaningful equity in a high-growth startup
- Strong in-person culture: 3–5 days/week in our London, SF, and NYC offices
- Flexible PTO to fully recharge
- Annual learning & development budget
- Frequent travel opportunities across the U.S., London, and Europe
- Bi-annual company offsites, twice-weekly team lunches, and monthly socials
- Company lunches twice a week
- Clear, accelerated growth opportunities as the company scales rapidly
- Comprehensive health, dental, and vision coverage
Company HQ
North Beach, San Francisco
Articles
Leadership
Eric Landau
(CEO)With MScs from Harvard and Stanford, Eric spent 8+ years as a senior quant at DRW deploying ML at scale—before co-founding Encord to make data the core of AI development.
Ulrik Stig Hansen
(President)Ulrik spent 3+ years in Sales & Trading at J.P. Morgan and holds science master’s degrees from UCL and Imperial—before co-founding Encord to transform how AI handles data.
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