GTM Engineer

About Fonzi AI

We're a well-funded, fast-growing startup backed by Lightspeed Ventures, revolutionizing hiring through AI. We've built a thriving marketplace connecting thousands of top engineers with 50 companies, and we're already revenue-positive with multiple successful placements. Our vision is to build an AI-powered recruiting marketplace that will connect millions of candidates and companies, where AI recruiters learn what you do, what you're interested in, and match you to perfect opportunities automatically.

The Problem You'll Solve

We've gained real momentum with our Match Day model. Now it's time to build infrastructure that unlocks our next phase - scaling from dozens to thousands of participating companies.

Here's the ambitious part: We don't have a proven playbook for this yet. We know we need to identify AI companies raising funds, enrich their data, score hiring intent, and intelligently orchestrate engagement across channels. But the way those pieces work together as one decision system? That's what you'll build. We have multiple channels that work in isolation (email, LinkedIn, ads, events). Your job is to build the unified engine that determines the right message, timing, format, and channel for each prospect - not as separate silos, but as one intelligent system. Some companies get a paid ad. Others get a personalized email. Others get an event invite. Others get content. The system decides what works for whom and why.

What You'll Build

• Company Intelligence: Build the data infrastructure that identifies AI companies entering the market, monitors funding rounds, tracks organizational changes, and surfaces hiring signals. You'll evaluate and implement tools like Clay, Instantly, and others - but you own the decisions about what data matters and how to use it.
• Enrichment & Scoring Engine: Design systems that transform raw prospect data into actionable signals. You'll create workflows that enrich company and hiring manager information, build scoring models that predict hiring intent and engagement propensity. This is where the magic happens - scoring not just "do they have engineers to hire" but "what's the likelihood they respond to an ad vs. a direct email vs. an event invite?"
• The Engagement Decision Engine: This is the new part - there's no off-the-shelf solution for this. You'll build the system that routes engagement intelligently across all channels. It ingests company data, propensity scores, and historical performance (what worked for similar companies), then decides the optimal way to reach each prospect. You'll iterate constantly - test ad performance against email, compare event invites to content plays, measure what actually drives pipeline. The system learns and improves over time.

What Makes This Hard (And Why We Need You)

• This isn't a "plug in Clay and call it done" role. You're building something we've never done before. Early on, you might find that the data doesn't tell you what you thought, or that a channel you expected to work doesn't. You'll need to get comfortable with ambiguity, run experiments fast, and iterate based on real results.
• The first 30 days might be messy - you'll be discovering what the real problem is. The next 60 days, you'll build real infrastructure. By month 3 or 4, you should see a pattern emerging about what works. By month 6, you'll have a system that makes decisions we couldn't make manually.

The Technical Challenge

We need someone who thinks in systems, not tasks:

• Data Pipeline Architecture: Design flows from discovery → enrichment → propensity scoring → channel/message decision → action
• API Orchestra: Integrate Clay, CRMs, email platforms, ad networks, and our internal tools into one cohesive system
• Intelligent Routing: Build the decision engine - not just "send this outreach" but "determine if this prospect should get an ad, email, event invite, or content play"
• Experimentation Framework: Set up A/B testing and measurement so you can prove what works and iterate toward better decisions
• Revenue Analytics: Connect activity to outcomes - show exactly which engagement strategies drive pipeline

Who You Are

You Must Have:

• Engineering DNA: You've shipped production code and think in systems/automation
• GTM Fluency: You understand funnels, conversion, CAC, and pipeline velocity
• Builder Mindset: You default to "let me prototype that" vs. lengthy planning
• Startup Speed: You've thrived where shipping beats perfection
• 3 years building revenue-driving technical systems
• Comfort with Ambiguity: You don't need a perfect specification before you start - you learn by building

You Probably Have:

• Experience evaluating and implementing tools like Clay, Apollo, or enrichment platforms
• Python/Node.js automation skills
• B2B SaaS or marketplace experience
• Worked at the intersection of data and revenue
• Strong opinions about build vs. buy decisions
• Experience running experiments and learning from results

You Are NOT:

• A marketer who dabbles in code
• A traditional RevOps person without engineering skills
• Someone who needs existing infrastructure to be productive
• Someone who needs every problem to be solved before you start

Why This Role is Different

• Own the Entire Stack: You're not inheriting legacy systems or executing someone else's vision. Every decision is yours - from tool selection to data architecture to channel strategy. You'll evaluate what's best, not defend what came before.
• Build Something New: This decision engine doesn't fully exist yet. You're not optimizing something known - you're creating something Fonzi has never done. That means real ambiguity, real learning, and real ownership.
• Direct Revenue Impact: Your code directly generates pipeline. Build a better enrichment model? More qualified companies in your system. Find the right channel-message combination? Higher conversion rates. You'll see the impact immediately.
• Work with Founders: Direct collaboration with Yang (CEO/CTO, ex-Google) and Brett (President, multi-time founder & investor). Your ideas shape company strategy.
• Compound Learning: Understand how AI companies hire, what actually moves them to engage, which channels work when, and why. This knowledge is invaluable.
• Perfect Timing: Series A with proven traction, revenue-positive, and ready to scale. Early enough that you own the build, a robust runway and real traction to build on.

The Data Platform Vision

You'll architect our "Companies Intelligence & Engagement Platform" that will:

• Track thousands of AI-centric companies and their hiring signals
• Monitor funding rounds, job postings, and organizational changes in real-time
• Intelligently route engagement across all channels and formats - determining the optimal way to reach each prospect (direct outreach, paid advertising, event invitations, content, partnerships, etc.)
• Surface "hot prospects" through multi-signal intelligence
• Learn and improve over time based on what engagement strategies actually drive pipeline
• Power our evolution from marketplace to more sophisticated AI-driven recruiting systems

What We Offer

• Compensation: $160K - $200K base meaningful equity
• Location: Brooklyn, NY (3 days/week in office - Tues/Wed/Thurs)
• Team: ~15 people including multiple successful founders
• Culture: Move fast, ship daily, celebrate wins, learn from everything. We're okay with ambiguity in service of building something real.