Overview
You'll build and lead the enterprise sales function at ElevenLabs, selling AI voice and conversational agent technology to Fortune 500s and large enterprises. This is a player-coach role - you'll close your own deals while hiring and ramping a team of 3-5 enterprise AEs. You report to the GTM lead (Lauren Kiefer) and spend half your time in deals, half in management.
Role Snapshot
| Aspect | Details |
|---|---|
| Role Type | Player-coach sales leader (50% closing, 50% managing) |
| Sales Motion | Outbound-heavy enterprise, some inbound from brand |
| Deal Complexity | Strategic enterprise - multi-stakeholder, custom contracts |
| Sales Cycle | 4-9 months for enterprise |
| Deal Size | $200K-$1M+ ACV |
| Quota (est.) | $2-3M personal + team quota of $5-8M |
Company Context
Stage: Series C+ (719 employees, growing fast)
Size: 719 employees
Growth: Actively hiring across GTM, team described as "growing quickly" and "crushing numbers"
Market Position: Category leader in AI voice/audio - they built their own foundational voice models and are now extending into conversational AI agents (think AI phone agents, chatbots with realistic voices)
GTM Reality
Pipeline Sources:
- 30% Inbound - Brand awareness from creator community generates enterprise inquiries, but these are usually exploratory and need heavy qualification
- 60% Outbound - You and your team build lists of enterprise prospects (think: customer service orgs at banks, e-commerce brands automating support, healthcare systems)
- 10% Referrals/Partners - Some ecosystem motion but early
SDR/AE Structure: Likely some SDR support for top-of-funnel, but at enterprise level you're doing most of your own prospecting and multi-threading
SE Support: Shared solutions engineering team - you get technical support for demos and POCs but need to fight for their time
Competitive Landscape
Main Competitors: Google Cloud TTS, Amazon Polly, PlayHT, Descript, possibly Synthesia for video use cases. Also competing against "build it ourselves" with OpenAI APIs.
How They Differentiate: Most realistic, human-like voice quality. Purpose-built models vs. general-purpose cloud services. Speed of inference matters for real-time conversational agents.
Common Objections: "We can just use OpenAI's voice API" / "What about data privacy and where voices are processed?" / "This is cool but what's the actual ROI?" / "Our call center vendor already has voice AI"
Win Themes: Voice quality is noticeably better in blind tests. Latency matters for conversational AI. Flexibility to clone voices and customize. Moving fast while competitors are slower enterprises.
What You'll Actually Do
Time Breakdown
Your Deals (30%) | Managing Team (25%) | Hiring (20%) | Internal (15%) | Strategy (10%)
Key Activities
- Closing Your Own Enterprise Deals: You carry 2-4 active opportunities at $500K-$1M+ each. These involve months of stakeholder mapping, POCs, legal redlines, security reviews. You're on Zoom with VPs of Customer Experience, CTOs, and procurement people.
- Hiring and Ramping AEs: You're building this team from scratch. That means writing JDs, screening candidates, selling them on ElevenLabs, then spending 30-60 days ramping them (ride-alongs, deal reviews, coaching on objection handling).
- Deal Reviews and Forecasting: Weekly pipeline reviews with each rep. You're pressure-testing deal stages, pushing for next steps, calling BS when things are stuck. You also roll up forecasts to leadership and get grilled when deals slip.
- Setting Enterprise Playbook: You're figuring out ICP, messaging, demo flow, proof-of-concept structure, pricing/packaging for enterprise. Some of this exists but it's not fully baked. You document what works and train the team on it.
- Executive Relationship Building: You attend conferences, do customer advisory board dinners, build relationships with CIOs and innovation leads. Some of this seeds deals 6-12 months out.
The Honest Reality
What's Hard
- Undefined Playbook: Enterprise motion is newer for them. You're figuring out how to sell AI agents at scale while also managing people. No one's going to hand you a perfect process.
- Long, Complex Sales Cycles: Enterprise deals take 6-9 months and involve security reviews, data privacy negotiations, custom contract terms. You'll spend a lot of time waiting on legal and procurement. Deals will slip quarters.
- Managing While Closing: You have to hit your own number AND build a team. When you're deep in a $800K negotiation, you still need to do your rep's weekly 1:1. It's a grind.
- Market Education: Conversational AI agents are new. Many prospects don't know what's possible or how to think about ROI. You're doing consultative selling and category creation, not just feature comparisons.
- Talent War: You're hiring enterprise AEs in a competitive market. Good ones have multiple offers. You need to recruit hard and sell the opportunity.
What Success Looks Like
- You close $2-3M yourself in year one while hiring and ramping 3-5 AEs
- Your team hits $6-8M in year one (ramp period)
- You build a repeatable enterprise sales process with clear stages, POC criteria, and win/loss themes
- You create compensation plans, territory structure, and hiring profiles that scale
- You have 2-3 reference customers who will take calls for prospects
Who You're Selling To
Primary Buyers:
- VP/Head of Customer Experience or Customer Service (call center automation)
- Chief Innovation Officer or VP Product (conversational AI features in products)
- CTO or VP Engineering (developer tools, API integration for voice capabilities)
What They Care About:
- Voice Quality: Does it sound human enough that customers won't complain?
- Latency: Can it respond fast enough for real-time conversations?
- Scalability and Reliability: What happens at 10,000 concurrent calls?
- Data Security: Where is voice data processed? What about GDPR/HIPAA?
- ROI: What's the cost per minute vs. human agents? What's the automation rate?
- Integration: How hard is it to integrate with our existing call center stack / CRM / systems?
Requirements
- 8+ years in B2B SaaS sales with 4+ years selling to enterprise accounts ($500K+ ACV)
- 2+ years managing and building sales teams (hired AEs, set quotas, run pipeline reviews)
- Track record closing complex, multi-stakeholder enterprise deals (legal, security, procurement)
- Experience in AI, developer tools, infrastructure, or emerging tech categories (you need to be comfortable with market education)
- Strong exec presence - you can hold your own with CIOs and VPs
- Player-coach mentality - you're willing to carry a bag while building the team
- NYC preferred for in-person collaboration with GTM leadership and team (though open to remote for exceptional candidates)