Read Ai

Senior Software Engineer - Growth (Fullstack)

Seattle , Washington , United StatesFull timeSeniorPosted 12 days ago
Apply on Read Ai →

Sign into see who you know at Read Ai.

ABOUT READ AI:

At Read AI https://www.read.ai/we’re redefining how teams collaborate by bringing intelligence to every conversation. Our platform supercharges productivity across meetings, messages, and email, so work gets done faster, smarter, and with better focus. We integrate seamlessly with tools like Zoom, Microsoft Teams, Google Meet, Slack, and more, helping teams stay aligned and move forward, whether they’re in the same room or across time zones.

Backed by $81 million in funding from Smash Capital, Madrona, and Goodwater Capital, Read AI is growing. If you're excited to move quickly, ship often and care deeply about building a product people genuinely love using, not just one they tolerate, we'd love to meet you.

 

THE ROLE:

As a Senior Software Engineer on the Growth team, you'll own a critical piece of how Read AI tests, measures, and learns. This isn't a maintenance role — you'll be building and hardening the experimentation infrastructure that the whole company depends on to ship with confidence, while also raising the bar for data governance and metric trust across Engineering and Product.

You'll work closely with Product, Data Science, and Design to turn growth hypotheses into shipped, measurable experiments — you'll have real influence over the technical standards and tools the team adopts. This role also comes with a mentorship component: you'll actively invest in the growth of junior and mid-level engineers on the team.

What You'll Do:

Own experimentation infrastructure

- Build, scale, and harden the systems that power A/B testing and experimentation across the company

- Improve experiment trust and throughput — faster cycle times, cleaner instrumentation, fewer invalid tests

- Identify and personally resolve high-impact issues in the experimentation stack

Drive technical direction

- Evaluate new tools and approaches relevant to experimentation and data governance

- Build team consensus around what's worth adopting — and wha...