Principal Sales Engineer – Warehouse Robotics Systems
Skild AI · San Mateo, CA · San Mateo
CHECKED 3H AGO
Roboticsonsiteprincipal$100k–$300k
At a glance
Highlights
- Own system design and modeling that underpins every enterprise warehouse deal.
- Architect throughput, ROI, and workflow models to justify robotics systems.
- Influence product roadmap as voice between customers and engineering teams.
Ideal candidate
Passionate systems thinker who loves translating complex operations into clear business value. Thrives at the intersection of sales and engineering and enjoys shaping product direction from customer insight.
Requirements
- 7+ years of experience in sales engineering, solutions engineering, or systems engineering within warehouse automation, material handling, or supply chain technology
- Demonstrated expertise building throughput models, simulation analyses, or operational designs for automated warehouse systems (AS/RS, AMRs, conveyor/sortation, goods-to-person)
- Deep knowledge of warehouse operations: order fulfillment workflows, labor management, WMS/WCS architecture, inbound/outbound processes, and peak planning
- Proficiency with simulation or modeling tools (AutoMod, Emulate3D, FlexSim, or equivalent); custom modeling in Excel or Python a strong plus
- Familiarity with WMS/WCS systems and integration requirements (API, EDI, SOAP/REST)
- Ability to read and interpret facility drawings, floor plans, and AutoCAD files
- Exceptional communicator comfortable presenting to both VP of Operations and CFO-level stakeholders
- Willingness to travel to customer sites (~40-50%)
- Bachelor's degree in Industrial Engineering, Mechanical Engineering, Supply Chain, or related technical discipline; Master's or MBA a plus
- Background working with or for 3PLs, large-format retailers, or e-commerce fulfillment operations preferred
Lab profile
About Skild AI
Building general-purpose robotic intelligence that adapts robustly to unseen scenarios.
What they build
- General-purpose robotic intelligence
- Scalable foundation model for robot deployment
Known for
- Large-scale data-driven machine learning
- Robust adaptation to unseen scenarios
- Computer vision and manipulation
- Simulation and embedded systems