Overview
You're selling AI video surveillance software that detects shoplifters and suspicious behavior to retail store owners, supermarket regional managers, and pharmacy chains. You work directly with the founder, own the full sales cycle from first contact to signed contract, and help figure out what messaging and process actually works. The product integrates with existing security cameras to send real-time alerts when it spots theft patterns or flagged individuals.
Role Snapshot
| Aspect | Details |
|---|---|
| Role Type | Full-cycle AE (prospect to close) |
| Sales Motion | Outbound-heavy (80%+ self-sourced) |
| Deal Complexity | Consultative transactional |
| Sales Cycle | 4-8 weeks |
| Deal Size | $15-50K ACV |
| Quota (est.) | $75-100K/quarter |
Company Context
Stage: Early-stage (13 employees, backed by Silicon Valley investors per their site)
Size: 13 employees
Growth: Actively hiring first GTM hires, founder still heavily involved in sales
Market Position: Emerging player in AI security/loss prevention - competing against traditional security camera systems and manual monitoring, plus newer AI players entering retail theft detection
GTM Reality
Pipeline Sources:
- 10-20% Inbound - website inquiries from retailers googling "AI theft detection" or "reduce shoplifting", quality varies wildly from tire-kickers to serious buyers dealing with major shrink issues
- 80-90% Outbound - cold calling store managers, emailing regional ops directors, LinkedIn outreach to loss prevention heads at chains
- Minimal partner/referral flow at this stage
SDR/AE Structure: No dedicated SDRs - you're doing your own prospecting, list building, and qualification
SE Support: Founder or technical team member may join demos for complex technical questions, but you're expected to run most demos solo
Competitive Landscape
Main Competitors: Traditional security monitoring services, other AI surveillance startups, DIY camera systems with basic motion detection, manual loss prevention staff
How They Differentiate: AI-powered real-time detection vs passive recording, works with existing cameras (no hardware replacement), developed by ex-FAANG engineers
Common Objections: "Our cameras already record everything", "We have staff watching", "Is this legal/privacy compliant?", "What's the false positive rate?", "Can I just hire another security guard for less?"
Win Themes: ROI from shrink reduction (retailers losing 1-2% of revenue to theft), proactive alerts vs reviewing footage after the fact, integrates with current setup, AI credibility from team pedigree
What You'll Actually Do
Time Breakdown
Prospecting (45%) | Active Deals (35%) | Internal/Admin (20%)
Key Activities
- Cold outreach: 40-60 calls/day to store managers and regional directors, plus LinkedIn messages and emails. Most don't respond. You're trying to find stores bleeding money from theft who'll take a 15-min call.
- Product demos: 5-8 per week via Zoom showing the live camera feed interface, how alerts work, walking through shrink reduction case studies. You're selling both the tech and the ROI math.
- Deal progression: Chasing down decision-makers for security policy review, navigating IT approvals for camera integration, negotiating pilot terms, pushing contracts through their procurement process.
- Founder syncs: Regular check-ins with Nazım on what's working, which industries respond best, pricing feedback, competitive intel. You're helping shape the sales process as much as executing it.
The Honest Reality
What's Hard
- Getting past gatekeepers to reach the person who actually cares about shrink - store managers are busy and don't always prioritize your calls
- Privacy/surveillance concerns - some prospects uncomfortable with AI watching customers, need to navigate legal questions you're still learning yourself
- Early product limitations - expect bugs, feature requests that aren't built yet, occasional demo glitches that kill momentum
- No established playbook - you're testing messaging, qualifying criteria, and pricing in real-time with founder input but limited structure
- Proof burden - retailers want to see it work in their specific environment, which means a lot of pilots/trials that may not convert
What Success Looks Like
- Closing 2-3 deals per month in the $15-50K range once you hit stride
- Building a repeatable outreach cadence that consistently generates 10-15 qualified conversations per week
- Developing customer stories and case studies from early wins that make future deals easier
- Identifying which retail segments (grocery vs pharmacy vs jewelry) convert fastest
Who You're Selling To
Primary Buyers:
- Store managers and owners (small chains, independent retailers)
- Regional operations directors (larger chains)
- Loss prevention managers (enterprise retail)
What They Care About:
- Hard ROI numbers - if they're losing $50K/year to theft, will this system save more than it costs
- False positive rate - can't have alerts going off constantly for non-issues
- Integration friction - will IT need to overhaul their camera infrastructure
- Legal/compliance - is this tracking customers in ways that violate privacy laws
- Proof it works in their environment - jewelry store theft looks different than supermarket shrink
Requirements
- 2-4 years closing B2B deals, ideally in SaaS, security tech, or selling to retail/brick-and-mortar businesses
- Comfortable with high-volume outbound prospecting - this isn't an inbound-fed role
- Technical enough to demo software and explain AI concepts without sounding like a data scientist
- Thick skin for early-stage chaos - product will evolve, pitch will change, you'll hit dead ends
- Hustler mentality - founder wants "disciplined closer who plays to win", translation: self-motivated, competitive, won't wait for leads to appear
- NYC-based for in-person collaboration with founder and team