Enterprise Sales Lead

Overview

You're selling AI "Superhumans" that replace or augment SDR/BDR teams. Your buyers are CROs and VPs of Sales at growth-stage B2B companies. The product just launched publicly (Nov 2024), so you're figuring out the pitch, objection handling, and sales process in real-time. This is consultative, strategic selling with 3-6 month cycles.

Role Snapshot

Company Context

Stage: Series A ($40M total raised, $30M Series A from Battery Ventures in Nov 2024)

Size: 95 employees

Growth: Hiring aggressively across GTM. Product just launched publicly, so early days.

Market Position: Category creator. Competing against Conversica, Qualified, Exceed.ai, but positioning as more comprehensive (voice/video, joins live calls, runs demos).

Product: AI "Superhumans" with face/voice that:

• Qualify inbound leads on websites 24/7
• Join conference calls as active participants
• Run custom product demos
• Work in deal rooms alongside human reps
• Integrate with existing sales stack

Founder: Amanda Kahlow built 6sense to unicorn. She has strong network in sales tech, which helps with credibility but also raises expectations.

GTM Reality

Pipeline Sources:

• 30% Founder/executive network (Amanda's 6sense relationships)
• 20% Inbound (website, content, some early buzz from $30M raise)
• 50% Outbound (you're hunting)

SDR/AE Structure: Likely self-sourcing initially, though they may be hiring SDRs. At 95 people, SDR team is probably small or nonexistent for enterprise.

SE Support: Probably shared SE or you're doing your own demos early on. Product is complex (AI agent configuration, integrations), so technical support likely exists but is stretched.

Sales Team Maturity: You're one of the first enterprise reps. There's no playbook. You're defining territory, ICP, pitch, demo flow, etc.

Competitive Landscape

Main Competitors:

• Conversica (established, more mature, 8-figure revenue)
• Qualified (strong Salesforce integration, conversational marketing angle)
• Exceed.ai (outbound AI focus)
• Plus 30+ new "AI SDR" startups launched in 2024

How You Differentiate:

• Multimodal (voice + video, not just chat)
• Joins live calls vs just async conversations
• Can run custom demos (more than qualification)
• Founder credibility (Amanda built 6sense)

Common Objections You'll Hear:

• "We tried AI chatbots, they didn't work" (you need to show this is different)
• "Our buyers want to talk to humans" (you're fighting perception AI is impersonal)
• "Too risky - tech isn't proven yet" (you just launched, limited case studies)
• "We already have SDRs/BDRs - why replace them?" (budget/headcount conversation)
• "How does this integrate with our stack?" (integration concerns)
• "What's the ROI?" (hard to prove with limited data)

Win Themes:

• Scale instantly without hiring/training/ramp time
• 24/7 coverage (no time zone issues, no PTO)
• Consistent quality (no bad days, turnover, ramp)
• Cost savings vs human headcount
• Speed to deploy vs hiring cycle

What You'll Actually Do

Time Breakdown

Prospecting/Outreach (30%) | Active Deals (40%) | Internal (20%) | Learning/Feedback (10%)

Key Activities

• Prospecting: You're building your own pipeline. Target CROs/VPs of Sales at Series B-D companies with sales teams of 20-100. Cold outreach on LinkedIn, emails, maybe some cold calling. Expect low response rates (2-5%) because you're new and unproven.
• Discovery: Long discovery calls (60-90 min) to understand their sales org, pain points, tech stack, buying process. You're not just qualifying - you're educating them on what's possible with AI agents.
• Demos: Product demos are complex. You're showing AI agent conversations, voice/video interactions, integration setup. Demos are semi-custom - you need to tailor to their use case (SDR replacement? Lead qualification? Demo automation?).
• Multi-threading: Selling to CRO, but also need to get VP Sales, Rev Ops, maybe Sales Dev leader involved. Lots of meetings to align stakeholders. Political navigation.
• Proof of concepts: Many deals will require POCs (30-60 days). You'll work with CS/implementation team to set up, train the AI on their product, test it with real leads. This extends your cycle but is necessary.
• Objection handling: Lots of "this sounds too good to be true" skepticism. You'll spend time on security questions, integration details, what happens when AI fails, etc.
• Internal feedback loops: You're reporting back to product and marketing constantly: "Here's what prospects are asking for" or "Here's why we lost this deal." Your input shapes roadmap.
• Contract negotiation: MSAs, security reviews, procurement. Enterprise deals have legal/procurement hurdles. You'll spend time in red-lines and vendor onboarding.

The Honest Reality

What's Hard

• Category creation is slow: People don't know they need "AI sales superhumans." You're creating demand, not capturing it. This means longer sales cycles and more education.
• Limited proof points: Product just launched, so you have few case studies, G2 reviews (only 4 currently), or ROI data. Prospects will ask "who else is using this?" and you'll have a short list.
• AI skepticism: Everyone's been burned by bad chatbots. You'll hear "we tried this, it didn't work" constantly. You need to overcome AI fatigue.
• Technical complexity: Integrations with Salesforce, Outreach, Gong, demo environments, etc. Lots of technical questions you may not have answers to yet. Product is evolving fast.
• Unpredictable AI: Even with good training, AI agents will occasionally say something wrong or fail. You'll need to set expectations that it's not perfect, which makes selling harder.
• No playbook: You're figuring out ICP, pitch, demo flow, objection handling as you go. If you like following a proven script, this isn't it.
• Long cycles: Enterprise sales of new tech = 4-6 months minimum. Many deals will slip quarters. You need to be patient and persistent.
• Quota pressure: As early rep, you're expected to produce fast to validate GTM motion. But deals take time. This creates tension.

What Success Looks Like

• Close $750K-1.5M in ARR in year 1 (3-6 enterprise deals)
• Build pipeline of 3x quota ($2-4M)
• Average deal size $100K-250K ACV
• Contribute to sales playbook (what works, what doesn't)
• Land 1-2 "lighthouse" customers that become case studies
• Maintain 25-35% win rate on qualified opportunities
• Average 3-6 month sales cycle (not 9-12 months)

Who You're Selling To

Primary Buyers:

• Chief Revenue Officer (ultimate decision maker, budget owner)
• VP of Sales (day-to-day owner, cares about team productivity)
• VP of Revenue Operations (technical buyer, integration concerns)

Influencers:

• Sales Development / SDR Manager (user, but threatened by "replacement" narrative)
• Sales Enablement (cares about training, rollout)
• IT/Security (vendor review, data security)

What They Care About:

• ROI proof: Can you show cost savings vs human headcount? Productivity gains?
• Integration: Does it work with their Salesforce, Outreach, Gong, etc.?
• Risk mitigation: What if AI says something wrong? How do you ensure quality?
• Speed to value: How fast can they deploy and see results?
• Scalability: Can it grow with them (10 agents to 100 agents)?
• Team impact: Will their human reps resist? How does this affect morale?

Requirements

• 5+ years enterprise SaaS sales experience with track record of closing $500K+ ARR annually
• Experience selling sales/GTM tools (CRM, sales engagement, enablement, etc.) - you need to understand the buyer
• Comfortable with early-stage ambiguity - no playbook, limited case studies, product evolving fast
• Consultative selling skills - long discovery, multi-threading, strategic deal management
• Technical enough to discuss AI, integrations, APIs with technical buyers
• "AI enthusiast" (per job post) - you need to believe in the vision and sell it authentically
• Self-starter - you're building your own pipeline, defining your own process
• Comfortable with rejection and skepticism - you're selling something new and unproven
• Grit and speed - deals will stall, you need persistence to push through
• Based in North America time zones