Lead Customer Support Engineer

The Role

We want engineers with real depth in AI/ML and low level systems who see customer support as a product to be engineered, not a queue to be cleared. Think of this less as a support role and more as an engineering seat positioned right at the customer's side. We're hiring problem solvers, not ticket closers.

You'll sit on the engineering team and commit production code next to the people building the core platform. The one twist is that your priorities are drawn from what the frontier of customer reality teaches you. In this role you'll:

• Write code that compounds. Land bug fixes, new capabilities, and automation that lift the experience for every Parasail customer, not only the person who flagged the problem.
• Partner with customers directly. Jump into Slack, email, and live calls to help developers and ML engineers troubleshoot, tune, and design their inference workloads.
• Build the dashboards, internal tools, and automated workflows that let a small team deliver great support to a fast growing customer base, and show up sharply at the moments that matter most.
• Turn signal into a roadmap. Distill recurring field patterns into specific changes: documentation fixes, API improvements, and proposals for new features.

What We're Looking For

• 3+ years of experience in a customer facing technical role. A real area of strength. You go deep in either low level infrastructure or ML/AI, and you can hold your own in the other.
• Systems fundamentals. Comfort across operating systems, file systems, networking, performance profiling, distributed systems, and cluster management.
• Hands on AI/ML. You've trained models, squeezed performance out of inference, worked directly with GPUs, or built ML infrastructure yourself.
• A bias toward automating. When you hit a manual, repetitive process, your reflex is to engineer it away, and you have the chops to actually do it.
• Strong communication. You can walk a customer through a thorny systems issue, file a tight reproducible bug report, and write documentation that lands, all while coordinating internally to get the fix out the door.
• Nice to Have: Experience supporting or operating a developer facing platform or API. A track record of customer facing technical work: solutions engineering, forward deployed engineering, or similar. Familiarity with the modern inference stack (vLLM, TensorRT LLM, CUDA, Kubernetes, or comparable tooling).