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Head of Sales, Digital Native

AssemblyAI· Sales
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Hybrid (Remote - San Francisco)$350k - $450kFull-timePosted 4w ago

About the role

Head of Sales leading the digital native and AI-native segment at AssemblyAI. Build and scale the digital native sales organization, own the land and revenue growth for the segment, hire and develop front-line managers, design coverage and comp plans, and drive an outbound-focused GTM motion in a technical, product-led environment.

Responsibilities

  • Build and lead the digital native sales organization - scaling from a small team of AEs and BDRs today to a larger sales org within the next year
  • Own the land number for the segment, focusing on bringing in net new customers and helping them scale up their usage in production
  • Hire, onboard, and develop front-line managers; establish the bar, the interview loop, and the ramp plan that make new AEs productive in weeks rather than quarters
  • Design the segment's coverage model - territories, target account tiers, and specialization across a large digital native account list where every company has a real production voice use case
  • Build the operating system for the team: forecasting, pipeline inspection, deal reviews, quota and comp design, and the metrics that tell you early whether the org is on track
  • Partner with Applied AI Engineering and Forward Deployed Engineering on the eval-to-production motion, so technical wins convert into deployed, growing usage
  • Work with Engineering, Research, and Marketing to shorten the time from product launch to real revenue
  • Drive an outbound-first culture where pipeline is created, not waited for, and where outreach earns replies through custom benchmarks, competitive insight, and use-case-specific demos
  • Represent the digital native voice of the customer to the leadership team and shape go-to-market strategy as new products launch

Qualifications

  • 8+ years in technical sales with 4+ years leading sales teams, including experience managing managers
  • A track record of scaling a sales org through a step change in headcount - hired and ramped 10+ reps and built the management layer underneath you
  • Experience selling infrastructure, APIs, or developer platforms to engineering and product buyers; ideally in a usage-based or consumption pricing model
  • Fluency with a product-led, bottoms-up motion that layers a sales team on top of self-serve adoption without breaking what already works
  • Technical credibility - discussing API architectures, model accuracy tradeoffs, latency, and deployment options with engineers/CTOs
  • Ability to design territories, quotas, and comp plans and to run a forecast
  • Recruiting instinct and ability to close candidates under pressure
  • High urgency and comfort with ambiguity; adapting to rapid changes in segment/product lines
  • Willingness to travel 50%+ of each month for customer visits, events, and team offsites

Skills

Required:Sales leadershipStrategic account planningForecasting and pipeline managementOutbound sales and go-to-marketTechnical credibility with engineers/CTOs

Benefits

  • Competitive equity grants
  • 100% employer-paid benefits
  • 401k match up to 4% for US-based full-time team members
  • Office options in San Francisco or New York City (onsite/remote considerations implied)
Last updated Oct 21, 2026. Interested? Apply on the company site.
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About AssemblyAI

APIs for AI models

AssemblyAI is an applied AI company. We research, train, and deploy State-of-the-Art AI models for developers and product teams to integrate into their products/apps. Today, we offer AI models for audio transcription, content moderation, summarization, topic detection, and many other tasks. We are working towards building the "Stripe for AI models" - where developers and product teams will be able to easily access State-of-the-Art AI through a simple API. We're a fully remote team of AI researchers and ML engineers, and have raised over $65M in funding from top investors including Accel, Insight Partners, Y Combinator, John/Patrick Collison, Daniel Gross, and Nat Friedman.

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