Head of Platform

About This Opportunity

We are representing a fast-growing AI infrastructure company in New Zealand that is building the platform layer for a global repair supply chain. Our client has recently completed a significant funding round and is scaling rapidly across multiple international offices. They need an experienced platform engineering leader to establish the foundations that will support their next phase of growth.

As Head of Platform, you will build and lead the team responsible for developer experience, reliability, cloud infrastructure, ML/AI compute, and security enablement. You'll treat platform as an internal product—setting strategy, driving adoption, and partnering with engineering teams to improve delivery speed, uptime, and cost efficiency. This role requires both strategic leadership and deep technical expertise across SRE, Kubernetes, cloud infrastructure, and increasingly, ML infrastructure and agentic development patterns.

Responsibilities

• Platform Strategy & Team Leadership: Build and lead the Platform function including SRE, DevEx, Infrastructure, and Security enablement. Set roadmap, establish practices, hire and grow the team, and manage prioritization trade-offs.
• Developer Experience: Create golden paths for engineers to build, test, deploy, and operate services. Implement service templates, CI/CD, environment provisioning, secrets management, deployment patterns, and feature flags. Drive measurable improvements in developer productivity.
• Reliability & Operational Excellence: Own reliability foundations including observability (metrics/logs/traces), alerting standards, incident response, postmortems, SLO/error budget practices, rollout/rollback patterns, and DR planning. Reduce on-call toil.
• Infrastructure Foundations: Ensure cloud and Kubernetes foundations are scalable, secure, and maintainable. Use Infrastructure-as-Code and automation (Terraform for GCP, GitOps with ArgoCD, Python/Bash tooling) for repeatable, auditable infrastructure.
• ML & Foundation-Model Infrastructure: Build the platform beneath foundational AI models—GPU/TPU provisioning, scheduling, training/fine-tuning orchestration, and scalable model serving. Own ML deployment lifecycle (model registry, experiment tracking, evaluation) and treat inference economics as a first-class cost driver.
• Agentic & Forward-Deployed Enablement: Design the platform to natively support agentic development with self-service, machine-consumable golden paths. Enable AI coding agents and distributed engineers to move from generated code to production with isolated execution environments, guardrails, and observability built in.
• Security Enablement: Partner with security/compliance to make secure-by-default the easiest path through IAM patterns, secrets management, vulnerability management, policy-as-code, and audit automation.
• Cost & Performance Ownership: Establish FinOps visibility and guardrails, track cost drivers, and deliver optimizations that improve unit economics without sacrificing reliability or velocity.
• Cross-Functional Collaboration: Work closely with Product/Engineering leadership to understand bottlenecks, influence architecture, and ensure platform work translates into customer and business outcomes.
• Hands-on Delivery: Be technical enough to dive in, review designs, unblock incidents, prototype solutions, and set technical standards while building a team that doesn't rely on you as the single point of execution.

What We're Looking For

Essential qualifications and experience:

• Platform Leadership: Proven experience leading platform/infrastructure/SRE functions including roadmap ownership, stakeholder management, and team building in fast-moving environments. Balance reliability, developer productivity, security, and cost.
• SRE & Operations Expertise: Strong grounding in SRE practices (SLOs/error budgets, incident management, observability, capacity planning, resilience engineering) with track record improving uptime and reducing operational toil.
• Cloud & Kubernetes Depth: Deep familiarity running production workloads on major cloud platforms (GCP preferred) and Kubernetes. Design scalable infrastructure, debug systems issues, and make pragmatic build vs buy decisions.
• Infrastructure-as-Code & Automation: Hands-on expertise with IaC and GitOps workflows (Terraform, ArgoCD or equivalent) and software engineering ability to build robust tooling.
• Developer Experience Mindset: Treat platform as a product—define golden paths, simplify workflows, drive adoption through empathy and excellent documentation, and measure impact (lead time, deploy frequency, MTTR, change failure rate).
• Security-by-Default: Practical experience embedding security into platforms and SDLC (IAM, secrets, vulnerability management, supply chain hygiene). Bonus for compliance experience (SOC2/ISO).
• Strong Engineering Fundamentals: Solid CS and system engineering fundamentals (concurrency, networking, Linux internals, performance profiling, distributed systems, reliability patterns).
• ML/AI Infrastructure Depth: Familiarity with AI infrastructure stack—GPU/accelerator compute, training/fine-tuning orchestration, inference and model serving, MLOps (registries, experiment tracking, evaluations), and cost/performance trade-offs of running models in production.
• Agentic-Native Platform Thinking: Design platforms where AI agents are first-class users—machine-consumable golden paths, safe autonomous execution, and self-service that scales to high workload volume. Bonus for enabling forward-deployed engineers to ship rapidly without sacrificing robustness.
• Communication & Influence: Excellent written/verbal communication. Align senior stakeholders, explain trade-offs to non-specialists, and coach engineers across the organization.
• Ownership & Bias for Action: Create clarity in ambiguity, deliver outcomes, and take initiative. Comfortable being accountable for foundational systems.

Bonus qualifications:

• Experience scaling platform practices through rapid growth (multiple teams/services)
• Familiarity with GCP, ArgoCD, GitLab CI, Kafka, Postgres
• Experience building internal developer platforms, service frameworks, or multi-tenant platform capabilities

Note: If you don't have all the skills listed above but believe you could be outstanding in this role, please still apply. We especially encourage applications from underrepresented groups who may count themselves out prematurely.

How We Work With You

Our talent team at Get A Job.ai will guide you through the entire process:

• Submit your application through the Get A Job.ai platform
• One of our specialist recruiters will screen your background and discuss the role in detail
• If there's a strong match, we'll prepare and submit your profile to our client
• We'll coordinate interviews and provide feedback at each stage
• Please do not contact the employer directly—all communication should flow through Get A Job.ai to ensure the best experience for everyone

Pay

Compensation details will be discussed with qualified candidates during the screening process. Our client offers competitive base salary plus equity for all full-time employees.

Get A Job.ai is an equal opportunity recruiter. We work with clients and candidates from all backgrounds and do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.