Koahlabs
Software Engineer - Backend
San Francisco
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hirly's read of this role
- Role family
- Engineering
- Seniority
- Mid level
- Country
- US
- Work mode
- On-site / unstated
- First seen by hirly
- 1 Sept 2026
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the posting
Who We Are
Koah Labs is building the ad network to power the next generation of AI-native products. Our mission is to help publishers monetize and help advertisers reach the right audience — without compromising speed, UX, or privacy.
We’re a small, tight-knit team in San Francisco with backgrounds at X, Apple, Meta and early-stage startups. We’ve raised from top investors and are growing fast with real traction on both the publisher and advertiser sides of the marketplace.
Working at Koah means joining at the ground floor: you’ll ship code that shapes the company and the ecosystem we’re building. We move quickly, operate with high trust, and care deeply about craft.
Our Stack
Infra : Terraform, AWS, LGTM (Loki, Grafana, Tempo, Mimir), Tailscale, Cloudflare
Data : PostgreSQL, ClickHouse, Redis, Kafka, Python
Core Application : Ruby on Rails, React, TypeScript
SDKs : Flutter, React Native, Android, iOS
Example projects
Build scalable data models that support multiple impressions for an ad request allowing us to align publisher and advertiser interests
Design abstractions that allow us to experiment and ship new formats that allow for a flexible way of tracking engagement events
Build a low-latency frequency capping system to improve an end user's experience and prevent ad fatigue
Create schemas to represent high-volume ad bidding with ad exchanges to increase the diversity of the ad demand on platform
Evolve our real-time auction and ad-decisioning systems to improve publisher, advertiser, and user outcomes
You might be a fit if
You like debugging and optimizing performance
You are detail oriented and like to create good abstractions that others rely on
You enjoy experimentation, measuring, and creating reliable systems
You want ownership of foundational systems
You enjoy working closely with product and data science to turn ambiguous problems into measurable outcomes
Is this role actually a fit for you?
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