Warehouse Lead

Go-to-Market & Operations · Palo Alto · full-time Own an industry at Sycamore: find the enterprise problems worth solving, earn technical trust with the people who own them, and turn early deployments into durable revenue. About Sycamore Sycamore is building the trusted agent operating system for the enterprise. Our platform helps companies build, deploy, and orchestrate AI agents that take on real operational work, with the security and control large organizations need. We are a small, engineering-led team working directly with Fortune 500 enterprises. We have raised $65M from Coatue and Lightspeed, along with other investors and industry leaders. The role You will own Sycamore’s commercial results in one industry. That means finding the right customers, understanding their operations well enough to be useful in a technical conversation, running deals from first meeting through production deployment, and building the account relationships that turn a first workflow into a platform commitment. This is a technical commercial role at an engineering-led company. You will spend as much time with operators and engineers as with executives. You are expected to understand what our platform actually does, where it fits, and, just as importantly, where it does not yet fit. Overselling a capability we do not have costs us far more than a slow quarter. You will work alongside our Applied AI engineers throughout. They build the deployment; you own the customer relationship, the commercial structure, and the outcome. When a customer conversation reveals a repeated need, you bring it back so it can become a product capability rather than a one-off promise. Early customers in a new category do not arrive through a mature pipeline. You will do original work: identifying which companies in your industry are ready, finding the executive who owns the problem and the operator who feels it, and constructing a first engagement narrow enough to succeed and consequential enough to matter. Retail runs a high volume of repetitive operational decisions under thin margins and hard seasonal deadlines: assortment and pricing changes, supplier and purchase-order management, catalog and product-data quality, promotion setup, store and field operations, returns and claims, and customer-service escalation. The work is distributed across merchandising, supply chain, store operations, and care teams that rarely share a system of record. Retail also moves faster than most enterprise segments. Buyers will run a pilot in weeks rather than quarters, and they will judge it on peak-season readiness and hard operating metrics. That rewards a seller who can scope a first deployment tightly and prove value before the next planning cycle closes. What the work looks like In one week, you might: Map how a retailer moves from supplier data to an accurate live catalog, and identify where an agent removes manual data remediation without introducing pricing or compliance risk. Work with a store-operations or supply-chain leader on where agent-handled exceptions must escape to a human, and how that behavior should differ during peak season. Build the business case in retail’s own terms: margin impact, out-of-stock and overstock rates, time-to-market on assortment changes, cost to serve, and hours returned to store or care teams. Sit with an operations team to understand a workflow in enough detail to know which parts an agent can take on, which parts require human judgment, and where the approval boundary belongs. Work with an Applied AI engineer to scope a first deployment with clear users, success criteria, and a decision point, rather than an open-ended pilot that never concludes. Take a customer’s security, compliance, or procurement requirement and turn it into a concrete answer, working with our engineers on what we can evidence today and what we would need to build. Build an executive relationship past the initial champion, so the engagement survives a reorganization or a change in priorities. Bring a recurring customer requirement back to Product and Core AI with enough specificity that it can be evaluated as a platform investment. Structure a commercial agreement that reflects the value delivered and leaves room for the account to expand. What you will do Own pipeline, forecast, and revenue for your industry, from first contact through production deployment, adoption, and expansion. Develop original point of view on which companies in your segment are ready to deploy agents, and why. Run technical discovery alongside our engineers, reducing a broad AI ambition to a specific workflow with real users, permissions, risks, and measurable outcomes. Navigate enterprise buying: security review, procurement, legal, data protection, and the internal approvals that decide whether a pilot becomes a contract. Stay accountable after signature for adoption, measured value, executive communication, and renewal or expansion. Build the references, repeatable deployment patterns, and segment knowledge that make the next deal in your industry faster than the last. Represent Sycamore credibly with customers, partners, and the broader industry. What we are looking for 8-15 years of experience in enterprise sales, technical account leadership, or a commercial role with direct revenue ownership. We will make exceptions for exceptional people in either direction. Experience selling technical software into retailers, consumer brands, or e-commerce and supply-chain organizations, with an understanding of how merchandising, supply chain, and store operations buy differently. Comfort with retail’s operating rhythm: seasonality and peak freeze windows, thin margins, franchise and store-level variation, and integration with POS, ERP, and order-management systems. The technical credibility to hold a substantive conversation with engineers and security teams without needing an engineer in the room for every exchange. Evidence of early-stage commercial work: opening a segment, landing first customers for a product without an established category, or building a territory from very little. Strong discovery instincts. You can tell the difference between an interesting conversation and a real problem with a budget owner and a path to production. Executive presence and high EQ. You can earn trust with a COO, a head of operations, a CISO, and a staff engineer in the same week. AI-native. You use modern AI systems in your own work, and you can speak about agent capabilities and limitations from direct experience rather than from a deck. Comfort with startup ambiguity, broad ownership, and regular customer travel. A 30-minute introductory conversation. Two 60-minute conversations, one on how you find and develop enterprise opportunities and one on technical discovery for an agent deployment. A working session where you present a segment and account plan for a real part of your industry, using the research and judgment you would apply on the job. Own an industry at a company defining a new enterprise category. Sell a technical product to technical buyers, alongside engineers who deploy it with you. Work on deployments where the outcome is measurable operational change, not a shelf-ware license. Shape which problems Sycamore solves next through what you learn in the market. Join early enough to build the commercial playbook rather than inherit it. Receive competitive cash compensation and meaningful equity in the company you are helping build. Hard problems, real impact Trust architectures, memory systems, multi-agent coordination. The foundational layer that makes AI agents work in production. Small team, high ownership Every engineer shapes the product and the culture. No layers of process between you and the work that matters. Backed by the best $65M from Coatue, Lightspeed, Abstract Ventures, Dell Technologies Capital, 8VC, and notable industry angels. Grow with us Competitive compensation, meaningful equity, and a genuine focus on your growth as the company scales. #J-18808-Ljbffr