Overview
You'll lead enterprise sales for ElevenLabs' voice AI platform, managing a team of 4-6 AEs while carrying your own $2-3M quota. You're selling API integrations and enterprise licenses to large tech companies, telcos, and enterprises who want to embed realistic AI voices into their products or build conversational AI agents. You'll spend about 40% of your time on your own deals, 40% coaching/managing your team, and 20% on internal planning and forecasting.
Role Snapshot
| Aspect | Details |
|---|---|
| Role Type | Player-Coach Sales Manager |
| Sales Motion | Outbound-heavy with some inbound PLG expansion |
| Deal Complexity | Enterprise/Strategic |
| Sales Cycle | 4-9 months |
| Deal Size | $200K-$1M+ ACV |
| Quota (est.) | $2-3M personal, $8-12M team |
Company Context
Stage: Series D ($11B valuation, $781M total raised)
Size: 704 employees
Growth: Hit $330M ARR in 24 months (fastest AI infra company ever - took Twilio 8 years to get there). Just raised $500M in February 2025, tripling valuation from prior year. Hiring aggressively across GTM.
Market Position: Category leader in AI voice generation, but PlayHT, Microsoft Azure Speech, Google TTS, and Murf.ai are all competing hard. Market is exploding with the conversational AI agent wave.
GTM Reality
Pipeline Sources:
- 30% Inbound - Developers/product teams using free tier who hit scale limits, or enterprises coming direct after hearing about them
- 60% Outbound - Cold prospecting into Fortune 500 tech/telco/financial services companies. You're finding innovation teams, product leaders, and CX execs who are building AI agents or voice products
- 10% Partnerships - Growing channel with telcos (e.g., Deutsche Telekom deal) and system integrators
SDR/AE Structure: You'll have shared SDR support for outbound, but enterprise deals often require direct exec outreach. Your AEs will self-source 40-50% of their pipeline.
SE Support: Shared SE pool. In complex POCs, you'll compete for SE time with other deals.
Competitive Landscape
Main Competitors: PlayHT (closest in quality), Microsoft Azure Speech Services (enterprise safe choice), Google Cloud TTS, Murf.ai, WellSaid Labs
How They Differentiate: Best-in-class voice quality and naturalness. Leading in emotional range and multi-language support. First to market with conversational AI agent platform that competes with voice.
Common Objections: "We're already using Azure/Google", "Concerns about voice cloning ethics/misuse", "API costs at scale vs self-hosting", "Data privacy for enterprise use cases"
Win Themes: Voice quality is noticeably better in demos. Speed to market vs building in-house. Multi-language/accent support. Growing agent platform for full conversational AI.
What You'll Actually Do
Time Breakdown
Your Deals (40%) | Team Management (40%) | Internal (20%)
Key Activities
- Managing Your Own Enterprise Pipeline: You're carrying 8-12 active enterprise deals. You're doing discovery calls with VP Products or Head of CX at large companies, running executive demos, navigating multi-stakeholder buying committees, negotiating contracts, and dealing with procurement/legal. Most deals involve custom MSAs and security reviews.
- Hiring and Ramping AEs: You need to hire 4-6 enterprise AEs in the next 12 months. That means screening 100+ candidates, running interviews, making offers, then onboarding and ramping each new hire. First 90 days you're riding along on their calls and helping them land their first deal.
- Weekly 1:1s and Deal Reviews: Every AE gets a weekly 1:1 where you're reviewing their pipeline, coaching on stuck deals, and role-playing objection handling. You're also running a weekly team forecast call with the VP where you commit to the quarter's number.
- Building Playbooks and Processes: The team is scaling fast but GTM is still being figured out. You're documenting what works (discovery frameworks, demo flows, competitive battle cards), standardizing the sales process, and feeding product/pricing feedback to leadership.
The Honest Reality
What's Hard
- High-growth chaos: Glassdoor reviews mention "need to know basis" communication and "immature leadership." Product and pricing are evolving fast. What worked last quarter might not work this quarter. Expect frequent strategy shifts.
- Long, complex enterprise cycles: You're selling into 5-10 stakeholders (product, engineering, legal, procurement, security). Deals take 6-9 months and often slip quarters because of security reviews or budget freezes. You'll spend a lot of time chasing procurement and legal.
- Competitive pressure: Microsoft and Google can bundle voice APIs into existing enterprise agreements. You're constantly justifying why companies should pay more for better quality vs using their existing cloud provider.
- Player-coach tension: Balancing your own quota with team development is hard. When you're heads-down closing a big deal, your team doesn't get coaching. When you focus on your team, your own pipeline suffers.
- Pricing/packaging in flux: AI voice pricing models are still being figured out. Usage-based vs committed spend, character limits, overage charges - expect pushback and negotiation on every deal structure.
What Success Looks Like
- You close $2.5M+ in new enterprise ARR personally in year one
- Your team of 4-6 AEs is collectively doing $10M+ ARR by end of year two
- 75%+ of your new hires hit quota in their first full quarter
- Your team's average deal size grows from $300K to $500K+ as you move upmarket
Who You're Selling To
Primary Buyers:
- VP Product / Head of AI at tech companies building voice features
- CX/Contact Center leaders at enterprises deploying AI agents
- CTOs / Engineering Directors evaluating voice API providers
- Innovation/Digital Transformation execs at Fortune 500 companies
What They Care About:
- Voice quality and naturalness (this is your wedge - demos sell themselves)
- Multi-language support and accent coverage for global rollouts
- API reliability and uptime at scale ("What happens if your API goes down?")
- Data privacy, security, compliance (especially for healthcare/finance)
- Total cost of ownership at scale vs alternatives
- Speed to production vs building in-house voice models
Requirements
- 8+ years enterprise B2B sales, with at least 3 years managing AE teams (4-8 reps)
- Proven track record selling APIs, developer tools, or infrastructure to technical buyers
- Experience with $200K+ ACV deals, 6-9 month sales cycles, and multi-stakeholder enterprise buying committees
- Comfortable being a player-coach - you need to carry and close your own quota while building the team
- Based in NYC preferred (they have an office there), but open to remote for the right person
- Deep understanding of AI/ML space and genuine interest in where voice AI and conversational agents are headed
- Ability to operate in high-growth chaos - things change fast, playbooks are being written in real-time