Pascal is a well-funded startup aiming to build AI-native systems for the offline economy, specifically targeting the CPG sector. They plan to create a foundational decision layer for finance, sales, and operations teams. The company is seeking founding engineers, indicating a significant and complex undertaking.
What they want, where you stand, and the exact résumé edits to qualify.
Biggest lever: Develop and demonstrate foundational system design skills specifically tailored to enterprise finance, sales, or operations in a CPG context.
A starter prompt for Claude Code, what you'll need, and how to reach them.
You are a senior founding engineer being evaluated for Pascal. Pascal aims to build AI-native systems for the CPG sector, creating a foundational decision layer for finance, sales, and operations. Your task is to outline a technical roadmap and a minimal viable product (MVP) for an AI-driven inventory optimization system for a mid-sized CPG company. Focus on the core components for data ingestion, AI model integration, and user interaction, assuming a Next.js 16 App Router, React 19, Tailwind v4, AI SDK v6 with Gemini, Neon Postgres on Vercel stack. Include considerations for initial data sources (e.g., sales data, historical inventory, supply chain metrics), the type of AI model suitable for forecasting and optimization, and how the output would be presented to a CPG operations manager. Specify the exact steps to build out this MVP, focusing on core functionality only. The build/verify gate is a demoable web application that can ingest sample CPG sales and inventory data, run an AI-driven optimization, and display recommended inventory levels for the next week, along with a rationale.
Pascal | Founding Engineer | New York City Pascal’s mission is to deliver AI-native systems to the offline economy, starting with the consumer packaged goods (CPG) sector. We are reinventing how they operate, building the foundational layer for decisions across finance, sales, and operations teams. We are ex-MIT founders who have built at startups that have grown from six to nine figures in revenue. We are well-funded from investors and angels of category-defining businesses (Decagon, Cognition, etc.) and hiring our initial founding engineering team! Apply: https://jobs.gem.com/teampascal-com/am9icG9zdDpZsQdF8LB3iyc2...
Build a small, targeted system (e.g., a data ingestion/reporting tool) that mimics a specific problem within CPG finance or sales, using publicly available CPG data or mock data. Focus on robust data modeling, API design, and a simple dashboard UI. Time: 4-6 weeks to MVP.
Extensive research and interviews into CPG supply chain, sales, and finance operations – ~1-2 months dedicated study.
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Familiarity with various ERP APIs (SAP, Oracle), EDI, and data warehousing patterns – ~1-2 weeks.
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Experience with time-series forecasting, optimization algorithms, and MLOps principles beyond basic LLM prompts – ~2-4 weeks to refresh/learn for specific CPG use cases.
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For production-grade Next.js deployments.
Standard database for Next.js applications.
Apply directly via the provided Gem.com link: https://jobs.gem.com/teampascal-com/am9icG9zdDpZsQdF8LB3iyc2...
“I'm a solo operator with deep expertise in full-stack development and AI integration, and I've developed a detailed technical roadmap and MVP concept for an AI-native inventory optimization system for CPG, leveraging the stack you're likely to use. I'm keen to explore how my hands-on build experience aligns with Pascal's founding engineering vision.”
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