
Job Overview
Location
San Francisco, Bay Area
Job Type
Full-time
Category
Sales
Date Posted
April 15, 2026
Full Job Description
đź“‹ Description
- • As an Enterprise Sales Lead at Partly Limited, you will drive the creation of new enterprise sales motions by identifying and landing anchor customers in untapped segments, directly shaping the company’s go-to-market strategy and product evolution through foundational deals.
- • Day to day, you will lead complex enterprise sales cycles from prospecting to close, design custom commercial structures including pilots and partnerships, collaborate with Product, Marketing, and Ops teams to translate field insights into scalable GTM motions, and ensure clean handoffs to regional teams after establishing repeatable processes.
- • Partly Limited is a scaling infrastructure company backed by top-tier investors including Blackbird Ventures, Square Peg, and Octopus Ventures, with strategic angels like Dylan Field (Figma) and Akshay Kothari (Notion), and engineering roots from Rocket Lab, serving hundreds of global automotive and industrial clients by modernizing the $1.9T replacement parts market.
- • In this role, you will build and validate new enterprise sales playbooks, gain deep exposure to product-led growth and infrastructure selling, develop credibility with C-suite stakeholders, and directly influence product roadmap and pricing strategy through customer feedback — positioning yourself as a builder of scalable motions rather than a maintainer of existing pipelines.
Skills & Technologies
About Partly Limited
Partly Limited operates a global marketplace and data platform that catalogs millions of auto parts from salvage yards, dismantlers and recyclers. It provides APIs and software tools that enable insurers, repairers and parts suppliers to identify, price and source OEM, aftermarket and recycled components in real time. Founded in 2020 in Christchurch, New Zealand, the company aggregates inventory from yards across North America, Europe and Oceania, applying machine-learning models to cross-reference parts numbers, fitment data and pricing for the collision and mechanical repair ecosystem.
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