Growth Manager

Emergent builds autonomous coding agents that replace traditional software development by generating, testing, and deploying production applications directly from plain-language intent. Our systems run in production at global scale and are used to build millions of real applications.

Since our public launch, we’ve crossed $130M in Annualised Revenue and grown to over 10M users across 190+ countries, who have built 12M+ applications on Emergent. We’re backed by Creaegis, Khosla Ventures, SoftBank, Lightspeed, Together, Y Combinator, Google, Claypond and Sentinel Global.

We’re solving the hard part of AI-driven software creation: correctness, reliability, security, and scale in real production systems. The team is built by repeat founders, Olympiad medalists, IIT & IIM alumni, and leaders from Google, Amazon, and Dropbox.

We’re hiring builders who want ownership, speed, and impact at global scale.

• →Own one KPI (e.g. retention, top-up rate, plan upgrades, or revenue per signup) with a weekly read of what moved and why
• →When a number breaks, find the root cause, the questions a standard dashboard can’t answer, size it, and say what to do about it
• →Analyze user behavior across cohorts, funnels, and segments to find levers across activation, credits and top-ups, pricing and plans, and churn
• →Design, run, and read experiments properly: hypothesis, sample size, holdouts, and the decision rule fixed before launch
• →Work with product, pricing, CRM, and marketing to ship what the data says
• →Use AI tools (LLMs, agents) to speed up your own analysis and to automate and personalize lifecycle interventions

• 2 to 4 years in growth, product, analytics, strategy, or a related role. Background is open; working hands-on with data is not
• Strong SQL skills, this is non-negotiable: you can independently query large datasets to build cohorts, funnels, and retention curves, and you validate your numbers before anyone else does
• Comfort living in data day-to-day: dashboards, product analytics tools, and spreadsheets are your home turf, and you form and test hypotheses from the data rather than waiting for someone to hand you an insight
• You’ve owned a metric and moved it, and you can show the before and after
• Working knowledge of experiment stats: significance, novelty effects, and when not to trust a result
• Comfortable using LLMs and AI tools in your day-to-day work

• Consumer or self-serve SaaS experience
• Python