Enterprise Account Executive

Overview

You sell an AI agent platform that automates revenue workflows to enterprise companies. You're joining as they launch a major new product, so you'll be building your pipeline mostly from scratch through outbound. Expect 6-9 month cycles selling into revenue operations leaders, VPs of Sales, and IT stakeholders who need to sign off on the technical integration.

Role Snapshot

Company Context

Stage: Series B+ ($50M+ raised)

Size: ~19 employees (early but well-funded)

Growth: Scaling enterprise team for major new product launch. Already at 8-figure ARR on existing platform.

Market Position: Category player in AI-powered revenue automation. Competing in a crowded but hot market with other AI workflow tools.

GTM Reality

Pipeline Sources:

• 20% Inbound - Some leads from existing product's brand awareness, but new product means limited MQLs
• 70% Outbound - You're building your own pipeline. Cold outreach to revenue ops and sales leaders at target accounts
• 10% Referrals/Network - Customer intros from existing base, investor network

SDR/AE Structure: Likely self-sourcing or minimal SDR support given team size. You own prospecting through close.

SE Support: Unknown - likely shared or limited given 19-person company size. You may be doing technical demos yourself or with founder/CTO support.

Competitive Landscape

Main Competitors: Other AI workflow platforms (6sense, Gong Engage, Clari), traditional marketing automation (Marketo, HubSpot), point solutions for specific workflows

How They Differentiate: AI agents that actually execute workflows vs. just providing insights. Cross-functional (sales + marketing + CS) vs. single-department tools.

Common Objections:

• "We already have [Salesforce/HubSpot/Outreach]"
• "How is this different from the 10 other AI tools we're evaluating?"
• Security/data privacy concerns with AI
• Integration complexity across their tech stack

Win Themes: Automation that spans the full revenue org, proven at scale (8-figure ARR), well-funded so they'll be around

What You'll Actually Do

Time Breakdown

Prospecting (40%) | Active Deals (35%) | Internal/Admin (25%)

Key Activities

• Cold Outreach: You're building lists of VP Revenue Ops, CROs, and VP Sales at companies with 500-5000 employees. Sending personalized sequences, making calls, working LinkedIn. You need to book 8-10 first meetings per month to keep your pipeline healthy.

• Discovery & Multi-threading: First calls are with revenue ops or sales operations leaders. You're diagnosing their current workflow pain points across systems. Then you need to expand into sales leadership (who controls budget) and IT/security (who'll block the deal if not involved early). Expect 4-6 stakeholders per deal.

• Demo & Technical Validation: You're showing how AI agents automate specific workflows they care about - lead routing, account research, sequence optimization, customer health scoring. Deals stall if you can't prove it works with their specific tech stack (Salesforce, Outreach, Gong, etc.). Expect to do a 2-3 week POC or technical deep dive.

• Negotiation & Procurement: You're navigating security reviews, legal redlines, and procurement processes. Deals that should close in Q2 slip to Q3 because IT security needs another meeting or their legal team requires MSA changes. Budget often gets pulled into their fiscal year planning, forcing delays.

The Honest Reality

What's Hard

• New product = cold prospecting: There's no big inbound engine for the new product yet. You're doing a lot of cold calling and LinkedIn outreach to people who've never heard of this specific platform. Most don't respond.

• Long, complex sales cycles: 6-9 months is real. You'll have deals that look great in March and still haven't closed by September. Lots of chasing for next meetings, waiting on procurement, stakeholders going dark for weeks. You need mental stamina for the long game.

• Crowded AI market: Every prospect is being pitched 5 other "AI-powered revenue tools" this quarter. You need to differentiate clearly and get them to actually see a demo instead of lumping you in with the noise. Expect a lot of "we're already evaluating AI tools" brush-offs.

• Startup chaos: 19 people means you're figuring things out as you go. Product roadmap may shift based on customer feedback. You might not have all the collateral, case studies, or competitive intel you want. You're building the plane while flying it.

What Success Looks Like

• Close $1.4M+ in new ARR annually (4 deals at $350K each, or 8 deals at $175K)
• Maintain a pipeline of 3-4x quota ($4-5M in qualified opportunities)
• Navigate enterprise procurement without deals dying in legal/security review

Who You're Selling To

Primary Buyers:

• VP Revenue Operations / Sales Operations (primary champion)
• CRO / VP Sales (budget holder, needs to see ROI on team efficiency)
• IT/Security Director (technical approval for AI tool accessing customer data)
• Occasionally: VP Marketing, VP Customer Success (if pitch is cross-functional automation)

What They Care About:

• Rev Ops: Reducing manual workflow tasks, improving data quality, making their team more efficient
• Sales Leadership: Rep productivity, faster ramp time, predictable pipeline generation
• IT/Security: Data security, integration complexity, vendor stability ("will this company be around in 2 years?")

Requirements

• 5+ years closing B2B software deals (you need to handle complex enterprise sales)
• 2+ years selling enterprise deals ($100K+ ACV) - you've navigated procurement, security reviews, multi-stakeholder buying committees
• Interest or experience in AI/ML products (you'll be explaining how AI agents work to skeptical buyers)
• Comfortable with startup ambiguity - you're not getting a polished sales playbook and 50-person enablement team
• San Francisco based and willing to work in-office (non-negotiable per the post)
• Self-starter who can build pipeline without heavy SDR support
• Technical enough to run demos and explain integrations, or willing to learn fast