About ngrok Inc.
ngrok builds developer infrastructure to connect services and AI models, wherever they run.
Most developers know us as the way to put localhost on the internet. More than 15 million of them use ngrok, at companies like GitHub, Okta, HashiCorp, and Twilio. It's the same ngrok they've loved and leaned on for years, now with the power to run production traffic at scale.
Teams use ngrok to deliver APIs, connect to their customers' networks, manage device fleets, and route traffic between public and local AI models.
Across all of it, we hold ourselves to one standard: developers should be able to finish a whole job without becoming experts in every system it touches. We take on the complexity, make thoughtful choices by default, and keep developers in control of what matters to them.
A few things you should know:
Our (unofficial) mascot is a shrimp. Yes, we make the puns.
We have a designated Chief Emoji Officer, and the role is vital to our success.
We like software that's serious and culture that's not.
Our competitive advantage is that we're having fun.
Still reading? Good. There's more below worth your time.
About the AI Gateway Team
Our AI Gateway team builds the systems that define how AI traffic is identified, controlled, and understood as it passes through ngrok.
We own the AI-specific control plane at the gateway layer: policies, usage tracking, and enforcement that sit directly on live customer traffic. Our systems must behave correctly under real-world conditions—traffic spikes, unexpected model behavior, misconfigured policies, and customers asking, “Why was this blocked?” or “Where did my tokens go?”
What You’ll Actually Do
Build and evolve the AI Gateway : You’ll work on the AI-aware gateway components that classify and handle AI traffic in real time. This code runs directly in the request path and must be fast, safe, and predictable.
Own AI traffic policy enforcement : You’ll design and implement AI Gateway Traffic Policy Objects—rate limits, usage caps, and access rules specific to AI workloads. These policies exist to prevent runaway costs, misuse, and accidental exposure without breaking legitimate traffic.
Track AI usage and token consumption : You’ll build and maintain systems that accurately measure AI usage—requests, tokens, and related metadata—so customers can understand how their AI systems behave and what they’re consuming.
Make AI behavior observable and explainable : You’ll expose clear, trustworthy signals around AI traffic: what was allowed or blocked, which policies applied, and how usage accumulated. When customers ask “what happened?”, the gateway should already know.
Design abstractions that hide complexity : You’ll work with product and design to build AI-specific gateway primitives that feel intentional and safe, without leaking provider quirks or infrastructure details into customer workflows.
Ship systems customers trust in production : You’ll collaborate closely with Gateway, Customer Data, and Platform teams to ensure AI usage data, policy enforcement, and billing signals line up—so customers can turn these features on with confidence.
You Might Be a Great Fit If…
You’re comfortable in a statically typed, compiled language such as Go, Rust, C++, or Java (with bonus points for Go)
Experience in frontend engineering, including expertise in TypeScript, React, HTML, CSS.
You’ve worked with AI/LLMs and can appreciate their unique brand of edge-cases
You care about developer experience and thoughtful abstractions
You enjoy defining system behavior, not just plumbing
You’ve thought about retries, limits, and costs before being asked
You like systems that move complexity from the user to the system
Extra credit if you’ve worked on:
AI platforms or inference infrastructure
API gateways with product-level opinions
Usage limits, quotas, or billing-adjacent systems
Customer-facing observability tools
Tech Stack
ngrok runs entirely on AWS. Engineers develop by using remote development…