SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
ngrok is an all-in-one cloud networking platform trusted by 9+ million developers at companies like GitHub, Okta, HashiCorp, and Twilio. The platform secures, transforms, and routes traffic to services running anywhere—from localhost sharing to production AI workloads.
The AI Gateway team builds systems that identify, control, and understand AI traffic as it passes through ngrok. You'll own the AI-specific control plane at the gateway layer: policies, usage tracking, and enforcement that sit directly on live customer traffic. These systems must behave correctly under real-world conditions—traffic spikes, unexpected model behavior, misconfigured policies, and customer inquiries about blocking or token consumption.
In this role, you will:
• Build and evolve AI-aware gateway components that classify and handle AI traffic in real time, running directly in the request path with strict performance and safety requirements.
• Design and implement AI Gateway Traffic Policy Objects—rate limits, usage caps, and access rules specific to AI workloads to prevent runaway costs, misuse, and accidental exposure.
• Build systems that accurately measure AI usage (requests, tokens, metadata) so customers understand their AI system behavior and consumption patterns.
• Create observable and explainable AI traffic signals: what was allowed or blocked, which policies applied, and how usage accumulated.
• Design abstractions that hide infrastructure complexity without leaking provider quirks into customer workflows.
• Collaborate with Gateway, Customer Data, and Platform teams to ensure AI usage data, policy enforcement, and billing signals align for production confidence.
You're a strong fit if you're comfortable in statically typed, compiled languages (Go, Rust, C++, Java—Go preferred), have frontend expertise in TypeScript/React/HTML/CSS, and have worked with AI/LLMs. You care about developer experience, thoughtful abstractions, and systems that move complexity from users to infrastructure. Extra credit for experience with AI platforms, inference infrastructure, API gateways with product opinions, usage/quota/billing systems, or customer-facing observability.
Tech stack: Go and TypeScript primarily, Postgres, Kafka, Protobuf, Kubernetes, Terraform, Helm, Buildkite, React, AWS, GitHub. Development uses remote tools and SSH to EC2 environments running a full Kubernetes cluster mirroring production.
