About the role
🚀 Our story Partly's mission is to connect the world's parts. We're building the first global platform for replacement parts — starting with automotive — and we're doing it with infrastructure-grade technology in a $1.9 trillion industry that's still running on manual workflows and legacy data. Founded by ex-Rocket Lab engineers, we've more than tripled our team in the last 12 months, with backing from Blackbird Ventures, Square Peg, Octopus Ventures, and personal investment from Dylan Field (Figma) and Akshay Kothari (Notion). Partly's solutions are live across hundreds of companies globally, providing the backbone for cataloguing and managing parts online. We're now building out our UK and European business — and we need the person who turns that growth into sharper decisions, credible forecasts, and confident bets on where to invest next. 🖍️ This role Automotive data is fragmented, inconsistent, and spread across dozens of formats worldwide. The Technical Solutions Engineer is the person who makes sense of it — working directly with enterprise customers to understand their data, their goals, and how Partly's AI platform can solve problems they've been living with for years. This is a rare blend of deep technical work and direct customer impact. You'll own the full data journey for enterprise clients — from ingestion and transformation through to live solutions — while partnering with Sales, Customer Success, Product, and Engineering to shape how Partly solves problems at scale. You'll report to the EU GM. 💻
What you'll do Work with enterprise automotive customers to understand their data and business goals, then apply Partly's AI platform to solve their most complex challenges Partner with Account Executives on evaluations and pilots — defining success metrics, leading technical conversations, and delivering outcomes customers talk about Build and demo solutions for real customer use cases that make the platform's value impossible to ignore Become the technical authority customers trust — providing clear architecture and integration guidance to engineering and data teams Feed insights back to Product and Engineering, turning what you learn in the field into roadmap influence Identify emerging patterns across customers and codify them into repeatable playbooks for the next deal 🥷 Your skills Proficiency in SQL and Python, with working knowledge of APIs, cloud platforms (AWS, GCP, or Azure), and data workflows Experience designing or deploying AI-powered products, including evaluation metrics and integration patterns Ability to explain technical concepts clearly to both engineers and non-technical stakeholders — and to know which mode you're in A hands-on builder mentality: comfortable prototyping quickly and finding pragmatic solutions under ambiguity Genuine customer obsession — you measure your success by theirs
