Senior AI Infrastructure Engineer

About the role

About Hellyeah AI Hellyeah is the agentic operating system for distribution. AI agents plan, execute and optimize growth work, and humans approve it. A small engineering team runs several live products, with coding agents as part of how we ship.

The role You will own the platform our products and agents run on: the gateway every model call passes through, the runtime for our production agents, and the clusters, data stores, pipelines, secrets and release paths underneath.

We're hiring two engineers, one in San Francisco and one in Shanghai. One will lean toward the AI platform and the other toward the core platform. You'll share ownership and on-call, and work closely with our CTO.

This role is onsite five days a week. On-call includes nights and weekends, and days often run past 10 hours.

Why this role: You'll own the whole platform, work directly with our CTO, and build the agents that run it.

We run production AI across text, speech and video, mostly through third-party model APIs, with some self-hosted serving. The gateway supports internal teams, our products and customers. We do not train models. If you only want to work on model training, look elsewhere. If you want to make a multi-provider AI stack reliable, secure and affordable, keep reading.

Product teams own product features. IT support, marketing sites and SEO sit outside this role.

What you'll do

The AI platform

- Run the model gateway. Own routing, fallbacks, provider failover, rate limits and rollouts for 90+ model deployments across OpenAI, Anthropic, Azure, Google and AWS Bedrock. Benchmark new providers on latency, quality, cost and failure behavior before they take traffic, and escalate to vendors when they fall short.

- Make the gateway multi-tenant. Give each team and customer the right keys, routes, limits and usage metering, and reconcile usage against provider invoices.

- Run the AI developer platform. Own shared coding-agent access, including seats, quotas and per-user limits, plus the remote workspaces our engineers use. One heavy user should never slow down everyone else.

- Run production agents safely. Own sandboxing, credential scoping and pinned releases for long-running agents on Kubernetes.

- Automate your own job. Expect to build a lot of autonomous infra workflows and infra agents that take on routine requests and alerts, with a person approving risky actions.

- Own infrastructure and AI spend. Reconcile provider bills against usage, tie spend to a team and product, and catch anomalies early. Right-size clusters, spend vendor credits before they expire, and handle quota and billing escalations with cloud and model vendors.

The core platform

- Keep clusters and cloud healthy. Debug and upgrade EKS, AKS and bare-metal k3s through Argo CD and Kustomize. Manage AWS, Azure and GCP through reviewed Terraform.

- Run the edge. Own Cloudflare across a dozen domains: DNS, WAF, TLS, CDN and object storage, plus GeoDNS, load balancers, egress IPs and email authentication.