P

Partly

Automotive parts data platform enabling marketplace

Product Engineer - Workshop

Full-TimeUpdated on 10/15/2026
No salary listed
Mid
Christchurch, New Zealand
In PersonOffice-first; daily office work is the default in Christchurch. Quarterly full-team gatherings require travel.
Software EngineeringFull-Stack Engineering

About the job

Requirements
  • A track record of taking features from idea to production, including writing code and being accountable for outcomes, with roughly 3+ years building and shipping production software.
  • A demonstrated habit of spending time with users in their work context and using that understanding to shape what is built.
  • Product judgment and craft in creating effortless experiences for time-pressured, non-technical users across fragmented, high-stakes workflows.
  • A point of view on agentic product design, including moving from manual operation to supervised delegation and earning user trust gradually.
  • Ability to build rapid prototypes independently, using AI-assisted tools as a first instinct for testing ideas.
  • Solid full-stack engineering skills with a frontend lean, production-quality coding, and sound fundamentals; systems-specialist depth is not required.
  • Ability to weigh product impact against engineering effort and identify lower-cost routes to results.
  • Analytical ability to define and build metrics views, interpret the data, and act on findings without waiting for a data team.
  • Ability to operate with ambiguity and autonomy and shape problems without waiting for a specification.
Responsibilities
  • Build product iterations by prototyping with AI-assisted and large language model-assisted tools, putting prototypes in front of customers before writing specifications, shipping production code, instrumenting it, and observing usage.
  • Spend time with customers in their work settings to understand the tasks, sources of wasted time, and what improvements would mean to them as a regular weekly activity.
  • Combine customer observations with data, reconcile conflicting signals, and use the resulting understanding to guide what to build next.
  • Own the product surface’s outcomes and metrics, including adoption and value delivered; prioritize work, explain decisions, diagnose issues, and fix them.
  • Balance product impact against engineering effort and identify efficient ways to achieve the desired outcome.
  • Move the product surface from manual operation toward supervised delegation by capturing user intent, determining where human oversight is needed, and building trust incrementally.
  • Maintain a high standard of product craft so the surface feels fast, clear, and considered, and challenge designs that do not feel right even when they function technically.
  • Pair with software engineers on more complex systems work and contribute to shared components, product craft, and team building practices.
Desired Qualifications
  • Experience shipping AI-assisted or agent-driven features in production, particularly where humans remain in the loop.
  • Experience building multi-persona, operational, or workflow-heavy business-to-business products.
  • Founder experience or experience as an early employee at a startup that scaled materially.
  • Experience abandoning or substantially changing a product or idea one personally believed in, with the ability to explain why.
  • Knowledge of automotive, the parts aftermarket, repair, or insurance claims.
  • Marketplace or network experience on the demand or supply side.
  • Rust experience or genuine eagerness to learn Rust.

About the company

Partly connects buyers and sellers of automotive parts through a B2B platform that serves as an online marketplace. It builds a global data infrastructure for the automotive parts industry, enabling manufacturers and retailers to organize, manage, and distribute parts data. The company uses data science and algorithms to process and standardize parts information from multiple sources, making it easier to find the right parts. Its platform treats data as the backbone of the ecosystem, supporting parts catalogs, data management, and supply chain transparency. Partly operates in New Zealand, Australia, and Europe with a global team and has attracted significant investor funding, helping it grow into a fast-growing startup in its region. The goal is to simplify the process of locating and acquiring automotive parts by improving data quality, interoperability, and connectivity across the parts ecosystem.

Company Size

51-200

Company Stage

Series B

Total Funding

$86.3M

Headquarters

Christchurch, New Zealand

Founded

2020

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Simplify Jobs

Simplify's Take

What believers are saying

  • Partly closed a $50M Series B on June 23, 2026, at $500M.
  • Austin headquarters relocation accelerates US hiring across engineering, product, and sales.
  • June 2026 launch targets 250,000 US repairers and a $100B collision market.

What critics are saying

  • CCC Intelligent Solutions and OEConnection dominate US repair workflows today.
  • Partly discloses no revenue, and its 2026 benchmarks remain self-published.
  • If OEMs restrict data access, Interpreter loses training fuel and commercialization stalls.

What makes Partly unique

  • Interpreter ingests photos, video, voice, and text for precise parts matching.
  • Partly trained on five years of repair data across 58 manufacturers.
  • OEM agreements and standardized parts data create a proprietary workflow moat.

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Benefits

Flexible Working Hours

Parental Leave

CycleSaver

Quarterly season openers across the UK and EU

Annual global offsite in New Zealand

Payroll Giving

Company News

iTWire
Aug 26th, 2026
Partly raises $71M to build AI that solves automotive parts matching challenges

Partly, a New Zealand-founded automotive AI company, has raised US$50 million in Series B funding led by DST Global Partners, valuing the company at US$500 million. The company has developed Interpreter, a multimodal AI model specifically trained to identify correct replacement parts for damaged vehicles. Unlike general-purpose AI models, Interpreter is built on five years of research using data from millions of vehicles and billions of parts. The company reports estimators using Interpreter achieved 98.8% parts-list accuracy compared with 92.1% using existing tools. The platform accepts text, photographs, video, and voice inputs to determine exact parts needed, accounting for variables such as trim level, production date, and regional differences. Partly is expanding into the United States, with headquarters in Austin, Texas, targeting America's US$100 billion collision-repair market. The company was founded in 2020 by Levi Fawcett, a former Rocket Lab engineer.

TechDay
Jul 21st, 2026
Partly raises $50M to double headcount and expand AI hiring in Australia

Partly has raised $50 million in Series B funding led by DST Global Partners, valuing the automotive software company at $500 million. Existing investor Blackbird Ventures also participated. The funding will support hiring in Australia, where Partly is adding software engineering, machine learning, and data science roles. The recruitment drive is part of an expansion expected to more than double global headcount this year. Founded in 2020, Partly develops an AI model called Interpreter for the automotive repair supply chain. The company has trained the model over five years using original equipment manufacturer catalogue data, repair data, and transaction data from New Zealand, Australia, the UK, and the Nordics. Partly targets a fragmented vehicle repair market where inaccurate parts data and manual procurement processes increase costs and delay repairs.

Yahoo Finance
Jun 23rd, 2026
AI startup Partly moves global HQ to Austin with $50M raise, plans 400 hires by 2028

Partly, an AI automotive startup, has relocated its global headquarters from the United Kingdom to Austin and plans to more than double its workforce over the next two years. The move was funded by a $50 million raise backed by Yuri Milner's DST Global Partners, pushing Partly's valuation to $500 million. Founded in 2020, Partly has built an AI model to automate workflows for vehicle repairs, serving automakers like Toyota and Hyundai. CEO Levi Fawcett cited Austin's talent pool and affordability compared to the Bay Area as key factors in the decision. The company currently employs about 50 people in Austin and expects 200 workers by end of 2027, doubling that number the following year. Partly will move into permanent downtown offices later this year.

SiliconANGLE Media
Jun 23rd, 2026
NZ startup Partly raises $50M at $500M valuation to crack US auto parts market with AI

Partly Group, a New Zealand startup using AI for automotive parts identification, has raised $50 million at a $500 million valuation and is launching its first US operation in Austin, Texas. Founded in 2020 by former Rocket Lab engineer Levi Fawcett, Partly has developed Interpreter, a foundation model trained specifically on vehicle parts. The multimodal AI reads technical diagrams, damage photos and repair descriptions, mapping them to standardised vehicle assemblies and part names across 91% of vehicles from 58 manufacturers. The company claims body shops using Interpreter process orders nine times faster and reduce returns by a factor of 2.4. The Series B round was led by DST Global Advisors, an early backer of Anthropic, Meta and Airbnb. Partly is targeting the US collision repair market, valued at over $100 billion across roughly 250,000 repairers.

NBR
Jun 3rd, 2026
Kiwi auto parts software startup Partly raises $90M at $900M valuation

Partly, a New Zealand auto parts software company, has raised $90 million in a Series B round, valuing the startup at $900 million. The funding places the company just short of the $1 billion valuation needed for unicorn status. Co-founder and chief executive Levi Fawcett said the company kept the capital raise confidential whilst gaining market traction.