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Partly

Automotive parts data platform enabling marketplace

Head of Platform

Platform EngineeringConfirmed live in the last 24 hours
Full-timeHybrid

About the Job

Requirements

  • Proven experience leading a platform, infrastructure, or site reliability engineering function, including roadmap ownership, stakeholder management, and team building in a fast-moving environment.
  • Strong grounding in site reliability engineering practices, including service-level objectives and error budgets, incident management, observability, capacity planning, and resilience engineering, with a track record of improving uptime and reducing operational toil.
  • Deep familiarity with running production workloads on a major cloud provider, preferably Google Cloud Platform, and Kubernetes; ability to design scalable infrastructure, debug systems issues, and make pragmatic build-versus-buy decisions.
  • Hands-on expertise with infrastructure-as-code and GitOps workflows, such as Terraform and ArgoCD or equivalent, and software engineering ability to build robust tooling.
  • Ability to define golden paths, simplify workflows, drive adoption through empathy and documentation, and measure impact using metrics such as lead time, deployment frequency, mean time to recovery, and change failure rate.
  • Practical experience embedding security into platforms and software development life cycles, including identity and access management, secrets, vulnerability management, and supply-chain hygiene.
  • Solid computer science and systems engineering fundamentals, including concurrency, networking, Linux internals, performance profiling, distributed systems, and reliability patterns.
  • Familiarity with AI infrastructure, including GPU or accelerator compute, training and fine-tuning orchestration, inference and model serving, machine-learning operations such as registries, experiment tracking, and evaluations, and production model cost/performance trade-offs.
  • Ability to design platforms for AI agents as first-class users, including machine-consumable golden paths, safe autonomous execution, and scalable self-service.
  • Excellent written and verbal communication, ability to align senior stakeholders, explain trade-offs to non-specialists, and coach engineers across the organization.
  • Ability to create clarity in ambiguity, deliver outcomes, act proactively, and be accountable for foundational systems.

Responsibilities

  • Build and lead the Platform function, including site reliability engineering, developer experience, infrastructure, and security enablement as appropriate; set a roadmap, establish ways of working, hire and grow the team, and manage prioritization and trade-offs.
  • Create the default path for engineers to build, test, deploy, and operate services, including service templates, continuous integration and delivery, environment provisioning, secrets and configuration, deployment patterns, and feature flags; drive adoption and measurable developer productivity improvements.
  • Own or drive reliability foundations, including metrics, logs and traces, alerting standards, incident response, postmortems, service-level objectives and error-budget practices, rollout and rollback patterns, backups and disaster recovery, and reduced on-call toil.
  • Ensure cloud and Kubernetes foundations are scalable, secure, and maintainable; use infrastructure-as-code and automation, including Terraform for Google Cloud Platform, GitOps with ArgoCD, and Python or Bash tooling, to run repeatable, auditable infrastructure.
  • Build the platform for foundational models, including GPU/TPU provisioning, scheduling and utilization, training and fine-tuning orchestration, scalable low-latency model serving, model registry, experiment tracking, evaluation and observability; manage inference costs as a key driver.
  • Design self-service, machine-consumable platform paths for AI coding agents and engineers, enabling generated code to reach production with isolated execution environments, guardrails, and observability; enable regional and forward-deployed engineers to work quickly on a robust, extensible foundation.
  • Partner with security and compliance teams to make secure-by-default practices the easiest path, including identity and access management patterns, secrets management, vulnerability management, policy-as-code, and audit-evidence automation.
  • Establish financial-operations-style cost visibility and guardrails, track cost drivers, and deliver optimizations that improve unit economics without sacrificing reliability or developer velocity.
  • Work with product and engineering leadership and stream-aligned teams to identify bottlenecks, influence architectural direction, and ensure platform work improves customer and business outcomes.
  • Contribute hands-on, particularly early in the role, by reviewing designs, unblocking incidents, prototyping solutions, and setting technical standards while building a team that does not depend on one person as its sole point of execution.

Desired Qualifications

  • Experience scaling platform practices through rapid growth across multiple teams or services.
  • Familiarity with the company's technology stack, including Google Cloud Platform, ArgoCD, GitLab CI, Kafka, and PostgreSQL.
  • Experience building internal developer platforms, service frameworks, or multi-tenant platform capabilities.
  • Experience helping achieve or maintain SOC 2 or ISO compliance.
  • Experience enabling forward-deployed or embedded engineers to customize and ship rapidly without sacrificing robustness.

About the Company

Partly

Automotive parts data platform enabling marketplace

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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