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Traba is building an AI operating layer for the industrial supply chain, starting with contingent labor and expanding into broader operational workflows. The company has embedded itself deeply in manufacturing and logistics operations, creating proprietary data from millions of shifts and strong enterprise relationships. Backed by Founders Fund, Khosla Ventures, and General Catalyst.
You will join as a founding member of the Agents team to build Traba's agentic platform—a system that synthesizes marketplace data and operates autonomously within customer supply chain workflows. This is a true 0-to-1 product role at the frontier of applied AI, comparable to Claude but purpose-built for light industrial businesses.
Key responsibilities include architecting product strategy for the AI agent platform, solving complex customer problems by balancing user needs against technical constraints and evolving AI capabilities, writing detailed product requirements, and partnering deeply with product engineers and ML teams. You will rapidly validate and prototype ideas with customers and design partners, design agent systems that reason through workflows, orchestrate tools, maintain context, and execute meaningful work. You'll define product behavior, evaluation systems, and quality frameworks to improve reliability and performance, use data to uncover patterns and answer critical product questions, and evolve the AI product portfolio with deep understanding of model capabilities and system architecture.
The ideal candidate has 7–10 years of product management experience with a proven track record launching products from scratch and driving meaningful customer outcomes. You must have experience building AI-native products or customer-facing agent systems—not just AI features, copilots, or chat interfaces, but systems that execute workflows, orchestrate tools, and perform work autonomously. You are a first-principles thinker comfortable operating in highly ambiguous startup environments with fast iteration cycles. Strong technical depth is essential; you should be comfortable working alongside ML engineers as peers, understanding evaluations, reasoning through system tradeoffs, and participating deeply in technical conversations. You believe the best products are built shoulder-to-shoulder with customers and have experience deeply embedding with early customers to understand workflows firsthand. You are inventive, scrappy, move quickly, embrace ambiguity, and know how to create meaningful outcomes without relying on large teams or excessive process. You work seamlessly across engineering, ML, operations, design, leadership, and customers.
This role reports directly to the VP of Product and offers the opportunity to shape the future of autonomous systems in industrial operations.
