Ai Traffic Engineer Jobs (NOW HIRING)

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?"

• 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're comfortable in a statically typed, compiled language such as Go, Rust, C++, or Java (with bonus points for Go)
• 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

ngrok runs entirely on AWS. Engineers develop by using remote development tools and/or ssh to connect to remote EC2 environments that run a full Kubernetes cluster of the ngrok stack, closely mirroring production. The codebase is primarily Go and TypeScript. We use Postgres for persistence, Kafka for streaming, Protobuf for service boundaries, and Kubernetes, Terraform, Helm, and Buildkite to operate and ship reliably. React is used for user interfaces, and GitHub supports our development workflows and remembers everything.

This is a remote position for candidates outside of the Bay Area and a hybrid role for candidates within commuting distance to San Francisco. Our Bay Area employees commute to the office on Tuesdays and Wednesdays.

All candidates must be US-based, and legally authorized to work in the United States.

At this time, ngrok is unable to provide visa sponsorship for this position. Applicants must be authorized to work in the United States on a permanent, ongoing basis without the need for current or future sponsorship.

Senior Software Engineer

• Tier 1 (SF, LA, Seattle, NYC): $202,500 - $247,500
• Tier 2 (rest of US): $186,300 - $227,700

Software Engineer III

• Tier 1 (SF, LA, Seattle, NYC): $180,000 - $220,000
• Tier 2 (rest of US): $165,600 - $202,400

Job level and actual compensation will be evaluated based on factors including, but not limited to, qualifications objectively assessed during the interview process (including skills and prior relevant experience, potential impact, and scope of role), internal equity with other team members, market data, and specific work location. We provide an attractive mix of salary and equity.

#LI-Hybrid