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. Eric Landau (CEO) comes from nearly a decade in high-frequency trading at DRW and quantitative research, with degrees from Harvard and Stanford. Ulrik Stig Hansen (President) started his career at J.P. Morgan and holds an M.S. in Computer Science from Imperial College London. Together, they founded Encord to solve the data infrastructure problem at the heart of modern AI.
Physical AI is our fastest-growing segment. Over the past 12 months, we've grown Physical AI revenue 10x. The companies building the next generation of robotics, autonomous vehicles, and intelligent physical systems have a data problem — and Encord is the only full-stack solution built to solve it.
We're now building the founding sales team that will take this to market.
This is a full-cycle commercial closing role on the ground floor of one of the most consequential verticals in AI. You'll own pipeline generation through close, selling into the world's most advanced Physical AI teams — robotics companies, autonomous vehicle programs, and research-driven enterprises like Boston Dynamics and Dyna. By day 30, you will have identified target accounts and booked meetings; by day 90, you will have closed your first pilot with a robotics or AV firm.
You'll report to the Head of Physical AI and work in close partnership with our founders and GTM leadership. Pipeline generation support is in place. Your job is to run deals with conviction and build the kind of customer relationships that compound over time.
This is not a role for someone who wants a defined playbook handed to them. It's a role for someone who wants to help write it.
What you’ll do
- Own the full sales cycle end-to-end, from outbound through close, with pipeline generation support
- Sell into Physical AI teams across robotics, autonomous vehicles, and research applications — from high-growth startups to large-scale enterprise programs
- Build deep relationships with technical and executive buyers: heads of autonomy, VP AI, ML engineering leaders, and data operations teams
- Develop a sharp point of view on the Physical AI landscape — understanding where customer pain is sharpest and how Encord's platform delivers measurable impact
- Partner closely with Product, Engineering, and Customer Success to bring customer insight back into the roadmap
- Help sharpen the ICP as we expand into new Physical AI use cases and geographies
- Forecast accurately, maintain pipeline discipline, and operate with the rigor of someone building something that will outlast them
Who we’re looking for
- A consistent top or near-top performer in your current or most recent sales role
- Comfortable selling technically complex solutions to skeptical, STEM-trained buyers — you don't need to be an engineer, but you can hold the room with one
- Energized by ambiguity and early-stage environments where you have real ownership and real accountability
- A natural relationship builder who earns trust through preparation, follow-through, and genuine curiosity about customer problems
- Entrepreneurial by disposition — you see gaps as opportunities, not blockers
- Resilient, high-output, and genuinely motivated by the quality of your work
Experience requirements
- 3 to 7 years in a B2B SaaS or enterprise technology sales role, with a track record of hitting or exceeding quota
- Experience selling to technical audiences — ML, data, or engineering teams — is a strong advantage
- Familiarity with data infrastructure, AI tooling, robotics, or autonomous systems is a plus, not a prerequisite; what matters is how fast you ramp and how deep you go
- Exceptional candidates from outside traditional SaaS sales will be considered: if you've performed at the top of a demanding, competitive field and can demonstrate it, we want to hear from you
Why Encord
- Competitive salary, commission, and meaningful equity in a high-growth startup
- Clear, accelerated growth opportunities as the company scales rapidly
- Strong in-person culture: 3–5 days/week in our newly launched North Beach loft office
- Flexible PTO to fully recharge
- 18 paid vacation days in the U.S. plus federal holidays
- Annual learning & development budget
- Comprehensive health, dental, and vision coverage
- Frequent travel opportunities across the U.S., London, and Europe
- Bi-annual company offsites, twice-weekly team lunches, and monthly socials
The data problem is the central bottleneck in AI. Not model architecture — data quality, data scale, and data infrastructure. Encord is the only company operating as a full-stack in AI native data infrastructure. Point solutions are losing. The market is consolidating around platforms, and we're positioned to win it.
Physical AI is the fastest-growing, highest-stakes segment in that market. The companies building robots, autonomous vehicles, and intelligent physical systems need a partner who understands 3D point clouds, LiDAR, sensor fusion, and video annotation at safety-critical precision. That's Encord.
You'll join at the inflection point — proven PMF, Series C momentum, and a category we're actively defining. The person in this role will have a direct line to the founders, real influence over how we go to market, and the kind of career acceleration that only comes from building something that matters at exactly the right time.
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What We Do
Encord is the data layer for physical AI. We're how the world's most ambitious AI teams turn messy, multimodal data into production systems - from humanoid robots to autonomous vehicles to smart infrastructure. 300+ teams including Toyota, Skydio, and Maxar rely on Encord to curate, manage, and align the data their models actually need. $110M raised. San Francisco, New York, and London.
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