<div class="content-intro"><p><span style="text-decoration: underline;"><strong>About Us</strong></span></p> <p>At You.com, we are building the AI Search Infrastructure that powers modern AI systems. Our goal is to create the trusted knowledge layer that agents, applications, and enterprises rely on to retrieve real-time, accurate, and citation-backed information.</p> <p>Our platform combines proprietary vertical indexes with LLM-optimized retrieval systems to power AI agents, applications, and enterprise workflows. We are solving hard problems across search, large language models, and large-scale infrastructure to make AI systems more reliable, transparent, and useful.</p> <p>Our team includes engineers, researchers, product builders, and operators who care about solving meaningful problems and delivering real-world impact. Whether you are improving core infrastructure, shaping product experiences, or helping bring new AI capabilities to market, your work will help define how modern AI finds and uses knowledge.</p></div><p><span style="text-decoration: underline;"><strong>About the Role</strong></span></p> <p>Every model call from our products and customers passes through one layer: our inference gateway. It allows users to select a model and we intelligently route the call to optimize on cost , latency and high availability. We are now building the control plane above it, to manage and govern access, performance and cost. </p> <p>You will own and scale that gateway. The work sits between model serving and product: routing and fallback across hosted providers and our own models, cache-aware routing decisions, metering accurate enough to bill on, and enforcement on the request path within a single-digit-millisecond budget.</p> <p>This is a remote position open to candidates based anywhere in the United States. We give preference to candidates in the San Francisco Bay Area or New York, where we have offices, but we are happy to consider strong remote candidates elsewhere in the US.</p> <p><span style="text-decoration: underline;"><strong>Responsibilities</strong></span></p> <ul> <li>Own the inference gateway that every model call routes through, including provider and model selection, fallback, and caps</li> <li>Build intelligence layer to autonomously pick the right model for the right turn in the task </li> <li>Make routing decisions that account for prefix-cache behavior, batching, and time to first token, not only price and availability</li> <li>Build cost attribution and metering across providers, including cached-token accounting, accurate enough to bill and enforce on</li> <li>Build request-path enforcement that degrades gracefully and never takes down a customer's inference call</li> <li>Ship inference-time changes in shadow mode first, with the measurement to prove they work</li> </ul> <p><span style="text-decoration: underline;"><strong>Qualifications</strong></span></p> <ul> <li>Hands-on production experience with model serving on stacks such as vLLM, SGLang (or similar platforms), with a working understanding of continuous batching, KV and prefix caching, and the tradeoff between time to first token and throughput</li> <li>You have tuned a serving stack against live traffic and know what moves p99 in practice, not only in theory</li> <li>Fluency across provider APIs: tokenization, prompt-caching semantics, and the differences in how usage and cached tokens are reported and priced</li> <li>Experience building or operating a proxy, gateway, or data plane on the critical path of production traffic, with sound instincts for failing open</li> <li>Comfort with streaming responses and the parts that get awkward: partial state, mid-stream failures, and work that can only happen once the stream closes</li> <li>A strong backend generalist (Python, Kubernetes). We expect you to pick up whatever you have not touched yet</li> <li>We weigh trajectory and recent growth more heavily than years of experience</li> </ul> <p><span style="text-decoration: underline;"><strong>Responsibilities</strong></span></p> <ul> <li>Experience at an inference provider or GPU cloud, or contributions to an open-source serving stack</li> <li>Fine-tuning and evaluating models in production</li> <li>Usage metering, billing, or cost optimization at scale</li> </ul> <p> </p><div class="content-pay-transparency"><div class="pay-input"><div class="description"><p class="p1">Our salary bands are structured based on a combination of geographic tiers and internal leveling. Compensation is determined by multiple factors assessed during the interview process, with the final offer reflecting these considerations.</p></div><div class="title">Salary Band</div><div class="pay-range"><span>$200,000</span><span class="divider">—</span><span>$250,000 USD</span></div></div></div><div class="content-conclusion"><h4><strong><u>Company Perks:</u></strong></h4> <ul> <li> <p>Hubs in San Francisco and New York City offering regular in-person gatherings and co-working sessions</p> </li> <li> <p>Flexible PTO with U.S. holidays observed and an end of year shutdown in December to rest and recharge*</p> </li> <li> <p>A competitive health insurance plan covers 100% of the policyholder and 75% for dependents*<