Founding Full-Stack Engineer

**Deepline** Founding Full-Stack Engineer; $180K–$220K base + meaningful equity (flex beyond for senior); New York City (On-site)

**About Company** Deepline is the operating system for GTM execution — a "Context API" that lets AI agents enrich, validate, deduplicate, and sequence across 40+ go-to-market data providers with a single call, replacing dozens of point tools and integrations. It's Cloud Code-native and API-first: customers don't log into a UI, they work through coding agents, and Deepline surfaces the right proprietary data point at the right time so the agent can solve the problem.

Backed by $3.3M pre-seed from Lerer Hippeau, K5 Global, Exceptional Capital, Sabrina Hahn, and Rohan Shah. Growth is ~100% month-over-month, with enterprise logos like Modal and Composio finding them inbound and spending quickly — thousands of power users across several Tier 1 companies, and strong PMF before a formal enterprise motion exists.

Small, senior founding team (Jai Toor, Saf, Chirag Toprani) out of Uber, Lyft, Capchase, Datafold and OM1, with pedigree from MIT, Waterloo, Berkeley, Princeton, and UCSD. Based in NYC, in-person.

**About the Role** You'd be engineer #5–6 and own a business problem end-to-end like a founder — not push features against a spec. Two vectors the team is most excited about: building the "machine that builds the machine" (using agents and automation to triage the 15–20 customer feedback requests that arrive daily, design fixes, and minimize human-in-the-loop), and acting as GM of a hard business problem (e.g. enterprise pricing). The current opening is weighted toward the frontend (a full-stack hire is moving into a forward-deployed role, and this backfills him) — still full-stack, but spiky on the front end.

**Responsibilities** - Own a business problem end-to-end — form hypotheses, experiment, iterate, ship. - Build the "machine that builds the machine": agentic/automation systems that triage and act on 15–20 daily feedback requests. - Write and ship production code daily, with strong frontend craft; manage coding agents and the codebase to deliver outcomes. - Turn raw customer feedback into product direction; help shape a fast-moving 2–3 month roadmap. - Extend the Context API and integrations across the 40+ GTM data providers.

**Required Skills** A. 3+ years building production systems, with clear velocity — promotions or fast-growing scope (e.g. 3→10+); senior, hands-on engineers strongly preferred. B. Strong full-stack engineering across Python (primary), TypeScript/JavaScript, and SQL — spiky toward the frontend for this seat (excellent React/TypeScript and product-UI craft). C. Heavy hands-on use of Claude Code / coding agents (near-prerequisite) — a real feel for where agents are strong and where they break. D. A "data mindset" — fluency reasoning about data access, modeling, and pipelines.

**Bonus Skills** - Data engineering or data science background. - Former founder or early-stage startup experience. - Familiarity with GTM tooling (CRM, enrichment, sequencing) or enterprise data systems.

**Logistical Info** - Location: NYC, fully in-person (5 days/week). Intense "marathons and sprints" culture with some weekend work — explicitly not a mandated 996. - Compensation: $180K–$220K base + meaningful equity; flexibility to go beyond for more senior candidates. - Number of openings: 2 (P0 — top priority). - Benefits/Other: TBC.

**Ideal Background** - Key filter is one strong "spiky" signal: elite school pedigree, a standout company logo, a side project with quantitative traction (GitHub stars, revenue), or a past startup/founder stint. Without a spike, hit-rate drops. - Strongest signal — intense, high-bar engineering cultures; Meta candidates have done well. - For this seat, frontend-spiky full-stack engineers (strong React/TypeScript, product-UI sensibility). - Big tech + 1–2 years at a startup is a great combination; data eng / data science backgrounds do well. - Velocity over tenure: promotions and growing scope; a former founder is an especially strong sign.

**Green Flags** - Former founder; high agency; reasons from first principles. - Already a heavy Claude Code / agent user. - Excited by traction and wants to "double down"; brings genuine intensity. - Intellectual curiosity (e.g. pursuing serious learning alongside work). - Wants to own a full business problem, not just close tickets.

- Trading/DeFi-protocol domain exposure (Brian, Aug 24: "Talos is a good parallel") — trading-experienced candidates strongly preferred over pure infra engineers. **Red Flags** - Slow-moving, "outside-looking-in" cultures — Salesforce and LinkedIn called out specifically. - 4–5 years at one company with no promotion or growth (low velocity). - No startup exposure / only comfortable in structured corporate settings (straight from big tech like Capital One is higher-risk). - Unwilling to work hard, including the occasional weekend.

**Interview Process** (fast by design; in-person in NYC) 1. Intro/screen (15–30 min) with Chirag — first sell and initial fit. 2. Technical interviews including system design (being updated from a generic "redesign DoorDash" prompt to a Deepline-specific problem). 3. Work trial / on-site in NYC. 4. Verbal offer delivered 1:1. Feedback within ~24h between stages.