Note: Partly is headquartered in the UK, with a Product and Engineering base in Christchurch, and an early presence in San Francisco. If you are not based in Christchurch, we will fly you to HQ for 2 weeks for onboarding, as well as 1 week per quarter for our “Season Openers” (we pay for your travel and accommodation). If you are relocating to Christchurch from NZ or from overseas, we can also assist with relocation costs.

🚀 Our story

Partly's mission is to connect the world's parts and we're doing that by building the first global platform for replacement parts, starting with auto parts. Our big vision is to accelerate the world toward a sustainable future where anyone can fix anything.

Founded by ex-Rocket Lab engineers, we utilise bleeding-edge technology to solve challenging but exciting problems that make a huge impact in a $1.9 trillion industry. We've more than tripled our team over the last 12 months and expect to double in size again over the coming 12 months. We're a global team spanning both Europe and Australasia.

We provide a scalable digital infrastructure solution to some of the world's largest businesses and the most exciting startups. Partly's solutions are integrated across hundreds of companies globally, providing the backbone for cataloguing and managing parts online.

Our investors in Blackbird Ventures (Canva, CultureAmp etc.), Square Peg, Octopus Ventures, Icehouse, Peter Beck (Rocket Lab), Akshay Kothari (Notion Co-Founder) and Dylan Field (Figma Co-Founder).

We're continuing to build a world-class team and ensuring Partly is a place where people can do the best work of their lives. We're proud of the culture we've built at Partly, and our values are lived throughout every experience.

🖍️ This role

Interpreter is Partly's own domain-specific AI model — purpose-built for the complexity of automotive parts. It is not a general-purpose model adapted for the industry. It is trained from the ground up on verified parts data, annotated by experienced mechanics, and designed to handle the fitment logic, catalog variation, and estimation formats that no general AI can reliably navigate.

This is one of the rare PM roles where you are not shipping features on top of someone else's model. You are helping shape a proprietary model for a physical industry — one where the output has direct consequences on repair cycle times, supplier operations, and insurer costs. Every downstream capability on the Partly platform depends on what Interpreter produces.

As Principal PM for Interpreter, you will own the accuracy, completeness, speed, and user experience of that output — and the value it delivers to repairers, suppliers, and insurers across the network.

You'll be operating at an inflection point. AI-assisted development and agents are compressing product discovery and delivery cycles. The best PMs we know are no longer waiting for engineering capacity to test an idea — they're building rapid prototypes themselves, deploying them, reading the signal, and deciding within days. We're looking for someone already working that way, or actively building toward it.

💻 What you'll own

• Parts Verification. The rate at which Interpreter correctly validates parts - the bedrock of trust across the network.

• Parts List Completeness. The rate at which Interpreter produces complete, job-ready parts lists across the full range of vehicle types, markets, and estimation inputs.

• Automation Rate. The proportion of jobs fully resolved by Interpreter without customer intervention.

• Loading Performance. User-perceived speed from VIN or job submission to actionable parts output, measured by p50/p95 response times and user-reported friction attributable to latency.

• Diagram Quality. The accuracy, completeness, and usefulness of the interactive diagrams and structured parts views surfaced to customers — working in close collaboration with Data Ops, who own the internal annotation loop that underpins them.

• Model Performance via the Customer Feedback Loop. The volume and quality of correction signals captured from real jobs, and the rate at which those signals translate into measurable accuracy gains over time across markets and vehicle populations.

💻 What you'll do

Own your product, end-to-end

• Define and evolve the product vision, strategy, and roadmap for Interpreter, aligned with company direction.

• Continuously assess and improve Product–Market Fit across repairers, suppliers, and insurers - a multi-sided network where each segment has distinct needs and expectations from the same underlying model.

• Own key product metrics across verification accuracy, completeness, automation, and performance - and use them to steer all decisions.

• Lead go-to-market alignment for Interpreter capabilities, including packaging, positioning, and rollout sequencing across markets.

• Act as the single accountable owner - for successes, failures, and everything in between.

Stay close to customers

• Maintain direct, regular contact with repairers, suppliers, and insurers - calls, site visits, usage sessions. This is a core weekly activity, not an occasional input.

• Talk to each segment separately; understand where their needs align and where they create tension.

• Combine qualitative insight with quantitative usage and metric data. Read both and reconcile them.

• Translate what you learn directly into prioritisation and PMF assessment - and share it with the teams that need it.

Build and ship, not just specify

• Prototype new product iterations yourself using AI-assisted development and LLM-assisted tooling - fast, disposable, real. We call this vibe coding; it is our default mode for product discovery.

• Treat the prototype as the hypothesis. Test with real customers before writing the spec.

• Run structured A/B tests and experiments where appropriate; use results to drive prioritisation.

• Work hands-on with data: define metrics, build dashboards, query logs, read the signals directly.

Lead in the human loop

• Partner closely with engineering leads to balance discovery, delivery, and technical sustainability.

• Collaborate with customer-facing experience teams to ensure Interpreter's value — AI outputs, confidence signals, and human review queues — is surfaced effectively at the UX and UI level.

• Communicate priorities and reasoning clearly — especially when the answer is no.

• Represent the customer's reality in every internal decision, not as a summary but as evidence.

Lead in the agent loop

• Own the customer-facing feedback loop: how AI confidence is communicated, how human review is prioritised, how customer corrections are captured, and how those signals feed back into model improvement.

• Define what "working" means for Interpreter's outputs - in terms of evals, edge case handling, and observable accuracy outcomes.

• Think in systems: a decision about how uncertainty is communicated to a repairer today affects the training signal quality that determines model accuracy tomorrow.

Raise the bar

• Contribute beyond your product boundary: cross-product coherence, shared principles, and the overall product craft at Partly.

• Help define what excellent product ownership looks like here as the team grows.

🥷 What you bring

Non-negotiables

• Proven experience as a product manager in a data-intensive or AI/ML product environment, with direct ownership of model-dependent user-facing products.

• Deep understanding of human-in-the-loop product design: how to structure review workflows, communicate model confidence, and close the feedback loop between user corrections and model improvement.

• Strong analytical capability — able to define, instrument, and reason from product metrics, and to distinguish signal from noise in model performance data.

• Experience working across technical and non-technical stakeholders, including close collaboration with engineering, data, and operations teams without owning them.

• Track record of driving measurable quality or accuracy improvements in a complex, domain-specific product.

• You build rapid prototypes yourself — with AI-assisted tools, LLM-assisted development, or code — as a first instinct for testing ideas.

• Excellent judgment under ambiguity. You commit, you course-correct, you own the outcome.

• 5+ years owning complex B2B software products end-to-end, with clear accountability for outcomes — not just delivery.

Strong signals we look for

• Familiarity with the automotive, collision repair, or parts supply chain industry — or demonstrated ability to develop deep domain fluency quickly in a technical vertical.

• Experience building products that serve a multi-sided marketplace, with an understanding of how value propositions differ across customer segments.

• Exposure to annotation pipelines, training data quality, or ML evaluation frameworks — enough to have informed conversations with data and model teams and understand how product decisions affect model outcomes.

• Experience scaling a product across multiple markets with meaningfully different inputs, workflows, or data characteristics.

• Comfort thinking in feedback loops, evals, and system-level instrumentation — not just user stories.

• Founder background, or early employee at a startup that scaled materially.

• You've killed or radically changed something you personally believed in, and can explain why.

Bonus

• Domain knowledge in automotive aftermarket, collision repair, or insurance claims.

• Experience with computer vision, multi-modal AI, or structured data extraction products.

• Experience building or operating products with meaningful agentic or automation components.

• Experience scaling products across multiple geographies or customer segments.

🧭 How you'll think and operate

We're not looking for framework experts or consensus-drivers. We're looking for someone who thinks like this:

• "I built a test version of the confidence UI this afternoon. Three repairers have already used it. Here's what I learned."

• "The correction rate on this vehicle cohort is an outlier. That matters more than anything in the backlog right now."

• "Here's what the data shows. Here's what I think it means. Here's what I'm doing about it. Here's when I'll be wrong." Speed, ownership, and judgment are the baseline. What differentiates the best candidates is the ability to operate fluidly across the human side — repairers, suppliers, insurers — and the technical one — model quality, data pipelines, evaluation frameworks — and to shrink the distance between intent and outcome.

🪅 Benefits

• Healthy, Catered Lunches - Enjoy fresh, healthy lunches every workday in our Auckland, Christchurch, London and San Francisco offices. With no meal prep needed, you can eat, connect, and refuel with your team. (And yes, snacks and drinks are always on hand.)

• Healthy Body, Healthy Mind - We care about performing at our peak. Every team member gets a $1,500 annual wellness allowance (or local equivalent) on a Partly-branded card. Use it on things such gym memberships, rock climbing, physio, massage, GP visits, prescriptions; anything that you or your family, need!

• Family Comes First - Primary caregivers receive 3 months of fully paid parental leave, plus a flexible return-to-work (four days on full pay for your first three months back).

• Getting Here Is On Us - If you commute to a Partly office or co-working space, choose from a paid 24/7 car park or commute allowance. One less thing to think about!

• Workspaces That Inspire - Our brand new, architecturally designed offices are built for collaboration and creativity, with great coffee, social spaces, and some of the best cafes a few steps away.

• Office-First with Flexibility - In cities where we have an office (Christchurch, Auckland, London, San Francisco), we default there every day. This lets us move faster, make better decisions and build strong relationships. We also operate with a very high trust environment, so you can manage your time around your life, and flex your schedule to get your best work done.

• We Celebrate Together - From weekly happy hours and monthly lunches to quarterly season openers and an annual global offsite, we make time to connect, celebrate, and have fun as one team.

• Take time when you need it. We don't ask questions or care if people have a negative leave balance. We work extremely hard and trust our team to take the time they need to recharge.