Software Engineer, Platform

We're building Skyway, a platform to help companies find, procure, manage, and forecast hyperscaler, inference, and GPU infrastructure. With the explosive growth of AI, companies are signing the largest infrastructure agreements in history and doing it all with spreadsheets and fingers-in-the-wind. Skyway provides structure and data to make the problem suck a whole lot less. Our customers are the strategic finance and engineering leaders at AI labs, inference providers, neoclouds, and AI-native software companies who are making seven, eight, nine, ten-figure compute decisions using data that flows through our systems. Under the hood, we're turning unstructured agreements—hyperscaler private pricing agreements, AI lab MSAs and prepaid credits, neocloud reserved capacity—into structured data, dynamically recalculating bills against both contract and public pricing, and giving finance and engineering a single shared set of numbers for what they've consumed, are consuming, and will consume. Our goal is to be the system every AI-native company runs its compute strategy on: forecasting, scenario modeling, commitment tracking, invoice validation, benchmarking, and purchasing, all on top of the best proprietary pricing dataset in the world. What you'll do Own the data infrastructure that powers everything. Build and maintain both streaming and batch data processing that process hundreds of millions of rows of billing data per customer, whether the data is streamed via OTel, near-realtime API pulls, or batched S3 ingestion. Build the contract application engine. Skyway doesn't just ingest consumption data—we also enrich and transform it substantially. You'll work on the logic that matches usage lines to contract terms, applies negotiated contract rates, and produces the financial outputs customers rely on. Getting this right is what separates us from being “a data pipeline with a graph on it” and a proper financial product. Become an expert on AI and cloud billing data. You'll master provider billing schemas, quirks, and evolution. You'll be diagnosing data anomalies regularly and documenting the tribal knowledge that makes this data so difficult to work with. Design the data model for multi-provider support. Each provider structures their billing data differently—different columns, different granularity, different pricing concepts. We ingest from a variety of source formats, such as OTel, APIs, and Parquet. You'll help make foundational decisions about how and when we normalize across providers, how we handle cross-provider queries, and how we keep provider-native detail accessible for deep dives. Build bulletproof data validation. Design quality control systems that catch issues before they reach customers. Financial data demands precision and a data quality bug can represent a customer breach in trust, not just an annoyance. Optimize for performance at scale. Design storage patterns, partitioning strategies, and query approaches that serve sub-second performance alongside heavy analytical workloads. Work across the stack. You'll collaborate with backend engineers on data contracts and APIs, help the product team understand what's possible with the data, and be the person who can answer “why does this number look like that?” when something seems off. This isn’t a throw-it-over-the-wall role—our platform engineers are core to everything we do. Our stack today is Python, ClickHouse, Airflow, Parquet on S3, with a Flask backend and React frontend. You’ll help us decide how this evolves, though we are quite keen on durable execution systems and embedded databases. What matters more than any specific tool is that you have strong opinions about data systems and the experience to back them up. How we work You’ll be given more autonomy than you’re comfortable with. Our engineering team is just six engineers today. People joining now are making foundational decisions that need to hold up to future growth in data and customers. We’ve got a lot to do and we hire for expertise and great judgement. We value quick decision-making and a “let’s find out!” attitude. We ship daily. New engineers ship in their first week. We value making progress toward customer desires every day. AI makes us all more capable. We use AI assistance throughout the company heavily and expect you to as well—not just tab-completion, but agents, code review, and whatever else helps you move faster. AI skeptics won’t do well here. About you You’re someone who builds data systems. You care about the people downstream of your work, whether they’re backend engineers, product, or customers. When data looks weird, you dig until you understand why, not just patch it. You have meaningful experience with data products, including warehouses, lakehouses, OLAPs, ETL pipelines, and semantic systems. You've worked with streaming or event-driven data as well as batch, and you have a point of view on when each is the right tool. Bonus if you've built systems that reconcile the two. You're strong in Python and SQL. You're comfortable with columnar databases and cloud storage. You're fastidious about data quality and comfortable when there's no answer key. You don't need to have domain expertise in cloud or AI billing. Upstream provider data sources have inconsistent documentation and are constantly changing. Instead, what matters is that you can figure things out without a spec and have a process for when schemas evolve underneath you. Compensation & Benefits Compensation for this role is a salary range of $200,000-$250,000 plus substantial early stage equity options. We provide a 401(k) and healthcare, vision, and dental with premiums fully covered by the company. Dependents are covered 50%. We offer 4 weeks of PTO, plus unlimited sick leave. #J-18808-Ljbffr Duckbill