work stack contact
GTM engineering · signal-based outbound

Vaibhav Kambli · GTM Engineer Portfolio

I turn noisy data into high-intent workflows — using Clay, Cursor, DeepSeek, and custom AI agents. building zero‑cost systems that feel researched, personal, and impossible to ignore.

case studies reach out
6+
GTM workflows
100%
AI‑augmented

· signal-led GTM ·

end‑to‑end engineering: from reverse hiring signals to negative‑review personalization — click any card to watch the full breakdown (video / LinkedIn post)

reverse hiring signals

claylinkedin adslead intelligence
  • targeted IT companies with 11–50 employees + $1M–$25M revenue
  • reverse hiring signals: new VP Sales hires → revenue pain
  • enriched with funding rounds, job openings, linkedin ads data
  • agent‑driven: top5 problems, employee achievements + twitter insights
click to watch LinkedIn video + full breakdown

zero‑cost workflow

cursordeepseekexa.ai
  • built own GTM stack instead of paying for expensive tools
  • exa.ai → discover 50 highly relevant niche companies
  • deepseek → enrich & structure data + key employees
  • cursor → full automation, zero credits burned
click to watch LinkedIn video + live demo

investor cold outreach

clayhubspotdeep personalization
  • targeted hedge fund managers, private investors (US/UK/CA)
  • data enrichment: bio, news, network, linkedin & twitter activity
  • transparent angle: “just starting out” boosted authenticity
click to watch LinkedIn video + results

natural ingredient signals

clayjob post intelligencepress release mining
  • targeting US food & bev manufacturers seeking natural ingredient suppliers
  • job openings: formulation scientists, R&D, clean‑label procurement
  • press releases: removing FD&C dyes → natural colors
click to watch LinkedIn video + methodology

review‑powered personalization

clayapi scrapingempathy-led copy
  • scraped auto dealers → extracted genuine negative reviews
  • context‑based subject lines: “customers saying you don’t respond to enquiries”
  • two email variations: direct + consultative approach
click to watch LinkedIn video + email walkthrough

Berlin pharmacy intelligence

clayrevenue signalsweak‑spot miningrisk scoring
  • location: Berlin + founding year + ad spend (Google/Meta)
  • key signal #1: recent senior‑level hire (growth or pivot)
  • key signal #2: large order received + company revenue​
  • bonus signal: known data leak? (security risk = opportunity)
  • scored every prospect based on these weak spots → revenue intelligence
click to watch Loom breakdown (Clay workflow)
GTM philosophy: I don’t start with leads — I start with signals. leadership changes, growth indicators, public job openings, review sentiment, and press activity → tailor outreach that solves actual problems, not generic pain points.

⚙️ engineering toolkit · built for performance & zero‑waste outbound

Cursor (AI IDE) DeepSeek Exa.ai Clay custom automations

Every workflow is built with scalability, cost‑efficiency and relevance in mind. I combine AI agents, scraping logic, and enrichment layers to build context‑first campaigns — no credits burned, just engineering.

let’s build signal‑first GTM 🚀

looking for a GTM engineer who automates personalization at scale? I turn raw data into revenue conversations — from reverse‑hiring signals to negative‑review outreach.

LinkedIn vaibhavkambli656@gmail.com calendly (demo workflow)
“GTM engineering is making personalization inevitable, not optional.”