Overview
You're the first sales hire at Salmon Labs, selling real-time AI-powered data infrastructure that keeps CRM and enrichment data current. You'll work directly with the CEO (Kevin Liu) and founding team to build pipeline through your own relationships and outbound, run full-cycle deals, and close. This is an early startup - expect to figure things out as you go and have real input on pricing, messaging, and who you target.
Role Snapshot
| Aspect | Details |
|---|---|
| Role Type | Full-cycle AE (player, not manager) |
| Sales Motion | Outbound-heavy / Relationship-driven |
| Deal Complexity | Consultative / Technical |
| Sales Cycle | 2-4 months (estimate - you'll help define this) |
| Deal Size | $50K-200K ACV (estimate - depends on use case) |
| Quota (est.) | Likely $800K-1.2M/year, ramped |
Company Context
Stage: Pre-seed/Seed (backed by Uncharted Ventures)
Size: Very small team (founding team + you)
Growth: Making first sales hire, building GTM from scratch
Market Position: New entrant in data infrastructure/enrichment space - competing against established players and internal scrappy solutions
GTM Reality
Pipeline Sources:
- 80% Outbound - you're sourcing through your network, cold outbound to RevOps/Data/Sales Ops leaders, and conferences/events
- 20% Founder network/referrals - Kevin and team will introduce you to some connections, but don't expect a full pipeline handed to you
- 0% Inbound - no marketing engine yet, minimal web traffic
SDR/AE Structure: No SDRs. You do your own prospecting, qualifying, demoing, negotiating, and closing.
SE Support: No dedicated SE. Founders will join technical calls when needed, but you need to be comfortable running product demos yourself.
Competitive Landscape
Main Competitors: ZoomInfo, Clearbit, Apollo, Cognism (established data enrichment vendors), plus internal data teams building their own pipelines
How They Differentiate: Real-time AI-powered updates vs. stale batch data. Most enrichment tools refresh quarterly or on-demand - Salmon keeps data current automatically.
Common Objections: "We already have ZoomInfo," "Our data team can build this," "How do I know your data is actually better," price vs. incumbents
Win Themes: Data accuracy/freshness, reduction in bad touches from stale data, time savings for RevOps teams manually updating records
What You'll Actually Do
Time Breakdown
Prospecting (40%) | Active Deals (35%) | Internal/Strategy (25%)
Key Activities
- Building your target list: Identify companies with large sales/CS teams that rely on accurate contact data. You're mapping out RevOps leaders, Data/Analytics VPs, and Sales Ops directors at B2B companies.
- Outbound outreach: Cold emails, LinkedIn messages, and calls to people you don't know. Expect low response rates early on - you're educating a market that doesn't know they need a "real-time data infrastructure" yet.
- Discovery and demos: Running calls to understand their current data stack (CRM, enrichment tools, workflows), showing the product, and articulating ROI. You'll need to get technical enough to speak credibly about data pipelines and integrations.
- Deal navigation: Multi-threading into data teams, RevOps, and sometimes sales leadership. Deals will stall when you can't get to the economic buyer or they prioritize other projects. You'll spend time chasing people for next steps.
- Pricing and packaging discussions: There's no rigid pricing sheet yet. You'll work with Kevin to figure out what deals are worth, what discount is acceptable, and how to structure contracts. This means deal authority but also figuring it out on the fly.
- Product feedback loops: When prospects ask "can it do X?" you're the voice back to engineering. Expect to be in Slack with the product team regularly.
The Honest Reality
What's Hard
- You're selling to people who already have enrichment vendors. Getting them to switch or add another tool requires proving real pain and clear ROI - not easy when they've already paid for ZoomInfo.
- No brand recognition. You'll hear "never heard of you" on most calls. You're explaining the category and the company at the same time.
- You're building the sales process from scratch. No playbook, no recorded demos to reference, no win/loss analysis to learn from. If you need structure and proven processes, this will frustrate you.
- Deals will take longer than you expect. Even if someone loves the product, procurement, security reviews, and "let's revisit next quarter" will push closes.
- You're alone. No other AEs to compare notes with, no sales manager coaching you. It's you and the founders.
What Success Looks Like
- Close 4-6 deals in your first year (realistic for early-stage, complex sales)
- Build a repeatable outbound motion: proven messaging, target personas, and pitch that others can eventually follow
- Get 2-3 reference customers who will talk to prospects and validate the ROI
- Establish pricing and packaging that the market accepts and that's profitable for the business
Who You're Selling To
Primary Buyers:
- VP/Director of Revenue Operations (budget owner, feels the pain of bad data)
- VP/Director of Sales Operations (manages CRM hygiene, enrichment tools)
- Head of Data/Analytics (technical buyer, evaluates data quality and integrations)
What They Care About:
- Data accuracy: How often are phone numbers wrong, emails bouncing, or job titles outdated?
- Time savings: How much manual work are their teams doing to keep records current?
- ROI: Can you quantify the cost of bad data (wasted calls, lost deals, poor segmentation)?
- Integration complexity: How hard is it to get this into their stack (Salesforce, HubSpot, their data warehouse)?
- Vendor risk: You're a new company - what happens if you shut down?
Requirements
- 5+ years selling data, CRM, sales/marketing tech, or intelligence products - you need to already understand this buyer and have relationships
- Full-cycle experience: You've built your own pipeline and closed deals before, not just worked inbound leads
- Comfort with ambiguity: No playbook, no defined ICP yet, no pricing sheet. You figure it out.
- Technical enough: You can speak to APIs, data integrations, and how data flows through a tech stack without sounding lost
- Self-motivated: No one is telling you what to do each day. You set your own activity goals and hold yourself accountable
- Existing relationships in RevOps/Sales Ops/Data communities: You can tap your network to get early conversations