Company OverviewParasail is redefining AI infrastructure by enabling seamless deployment across distributed GPU networks, optimizing for cost, performance, and flexibility. Our mission is to give AI developers a fast, cost-efficient, scalable cloud experience free from vendor lock-in.We build the company the same way we build the product. Parasail runs on agents, from kernel optimization through to how we answer questions about our own business, and this role sits close to the center of that.Role SummaryEvery inference request we serve is a decision about hardware, cost, and performance. Making those decisions well, at scale, across a distributed GPU fleet, is a data problem before it is anything else. The intelligence layer behind those decisions is one of Parasail's real advantages, and it is what this role owns.Our internal analytics are agent-native. Teams ask the business questions directly and get real analysis in minutes, on data infrastructure designed so that people and agents query it the same way. It is a different way to run a company, and it is a large part of why a small team moves as fast as we do.You will own and expand that layer. You will design the data models behind fleet and unit economics, build the analytical capabilities the rest of the company runs on, and turn questions that used to take a week into answers that take a minute. Work you ship compounds, because it becomes something the entire team can use immediately.You will work through MCP connections and agentic tools every day. We expect you to be productive in that stack from week one.Questions You Will AnswerWhat does a token actually cost us across hardware generations and workload profiles,



and where does that curve bend?Which workloads run best on which hardware, and what is that difference worth to a customer?Where is capacity earning, and where is it waiting, across every GPU and every region we operate in?How does a model's benchmark performance translate into real unit economics at production scale?As the fleet gets more efficient, how much of that can we hand back to customers as better pricing?Key ResponsibilitiesDesign and own the data models behind fleet economics, capacity, and utilizationBuild the analytical capabilities and reporting the company makes decisions from, and expand what our internal agentic tooling can answerBuild and maintain the pipelines that bring infrastructure, usage, billing, and customer data into one coherent viewDevelop dashboards and models connecting operational performance to revenue, margin, and capital efficiencyBuild verification into the data layer so answers stay trustworthy as the product evolves quicklyPartner with infrastructure, finance, product, and go-to-market to anticipate what they need to knowUse agentic tooling to automate analysis and reporting, and raise the ceiling on what one person can coverRequired Qualifications2 to 5 years in business intelligence, data analytics, analytics engineering, operations analytics,



or a similar hands‑on data roleStrong SQL, plus Python or a comparable language for data workDaily proactive use of agentic AI tools with MCP connections to pull data from source systemsReal curiosity about how a business works underneath the metrics, and the drive to chase a number until you understand it completelyTechnically literate enough to work directly with infrastructure and engineering teams and reason about what the systems are doingAbility to explain what the data says, and how confident you are in it, to any audienceHigh ownership and strong instincts for what is worth measuringExcited by a fast‑moving startup where you get to define your own scopeNice to HaveExperience in operations, manufacturing, logistics, or another environment where asset utilization and yield drive the businessCloud infrastructure, data center, GPU, or semiconductor exposureUsage‑based or consumption‑based billing experienceExperience building internal tools, pipelines, or automationFamiliarity with dbt, warehouse modeling, or observability toolingCompensation & BenefitsCompetitive base salary with meaningful equityComprehensive health, dental, and vision coverageGenerous PTO and company holidays401(k) and family‑planning benefitsHigh visibility with the executive team and direct exposure to how the business is runThe chance to build agentic data infrastructure that the entire company runs onParasail is an equal opportunity employer committed to workplace diversity and reasonable accommodations for qualified applicants with disabilities.
#J-18808-Ljbffr

📌 Business Intelligence Associate (San Francisco)
🏢 Parasail
📍 San Francisco