Finance Engineer at AssemblyAI in North America

Job description

Why AssemblyAI AssemblyAI builds the best-in-class Voice AI models powering the next generation of voice applications. We have a lab, and we also power our own models in our own proprietary inference environment. Our models serve 500M+ inference calls monthly, and process nearly 2 million hours of audio daily. The Voice AI space is at an inflection point; we’re looking for the best talent we can find to join a rapidly scaling team that's defining the future of the industry. We are one of the most capital-efficient AI companies on the planet - and are rapidly approaching $1M ARR per employee. We sit among the top 5 most revenue-dense teams within the fastest-growing AI companies today. We have thousands of customers building with us including the top startups and world-renowned enterprises, and are serving at tremendous scale: we process nearly 2 million hours of audio daily and handle more than 15 million API calls every day. This is a rare growth-stage opportunity where the business is proven, the revenue is durable, and the growth trajectory is steep and getting steeper. We have a super flat culture and expect our employees to be deeply intimate with the details at all levels. If you've ever felt buried under layers of bureaucracy, starved of real ownership, or frustrated watching your work disappear into a slow-moving org, AssemblyAI is built differently. The company operates as a true meritocracy, with no heavy planning or approval processes and no gatekeeping on the tools or information you need. For anyone who genuinely cares about voice AI, not as a trend to chase, but as a technology to build, this is the place where the most interesting problems at the most interesting scale are being solved by a team small enough that you'll actually know everyone's name. About the role: We're looking for a Finance Engineer to join our Finance team, building the data pipelines, dashboards, and automation that run the finance function and the revenue operations around it, from deal desk to sales compensation. Our goal is to operate finance as a small, senior team that runs on systems rather than headcount — and how well we do that depends on how quickly anyone here can get a trusted number on unit economics, cash burn, or technology spend and act on it. Building that capability is the heart of this role. You'll be working inside the numbers you're automating, not alongside them.The ideal candidate is an engineer first: strong data engineering fundamentals across SQL, Python, warehouse modeling, and orchestration, combined with enough finance and operational fluency to model revenue, cost, and margin without hand-holding. Experience building internal tools and agent workflows that non-engineers rely on daily is what sets this candidate apart. This is a cross-functional role. You'll work closely with the VP Finance, our Controller, sales leadership, and engineering and infrastructure leadership — not as a handoff point, but as the person who learns enough of each domain to follow a number back to its source. At times you'll build the model, run the analysis, and present the finding yourself, both to deliver impact directly and to learn what's worth automating next. The bar is someone who understands the decision a number is meant to support, measures it from the outset, and would rather find out a model was wrong in a week than at quarter close. That discipline is what turns cross-functional ownership into an advantage. The role is embedded within the Finance team and reports to the VP Finance. What You’ll Do: Own unit economics — build and maintain cost-to-serve, gross margin, and contribution models by product, customer, and workload, rebuilt from source data rather than spreadsheets. Own budgeting for the technology organization: cloud and GPU/TPU spend attribution, vendor and capacity forecasting, and the models engineering leadership uses to plan. Build and run finance dashboarding — a single source of truth for burn, runway, margi