The opportunity
Our rapid growth into new verticals and markets presents a fantastic opportunity to evolve our platform. We are building on our initial successes by transitioning to a highly scalable architecture that seamlessly supports our expanding customer base across diverse industries.
It’s an engineering opportunity to turn a carefully operated platform into a Kubernetes-native, self-service product. The goal is to serve internal customers first and deliver at high velocity with safe, capable self-service solutions aligned with the best practices of platform engineering.
It's a leadership opportunity in equal measure: you'll build and grow the team that owns it, and have an impact on how platform engineering is done here as the company scales.
What you'll own
Self-Service Enablement: Empower cross-functional teams with secure, automated pathways that accelerate development while maintaining organizational standards.
Architectural Modularization: Evolve our infrastructure into a decoupled, scalable architecture that supports rapid iteration and independent service lifecycles.
Unified Infrastructure Management: Implement a rigorous "Everything as Code" strategy, treating infrastructure, policy, and configuration with the same standards as application software.
Proactive Reliability: Foster a culture of operational excellence through robust observability, clear Service Level Objectives, high operational hygiene and safety.
What success looks like:
In 6 months: Lead the transformation to a self-service infrastructure platform. Target a 30% reduction in deployment lead times and a 50% increase in self-service adoption among R&D teams. Implement platform-wide observability and SLO monitoring to ensure 99.9% uptime for core services.
In 12 months: Evolve the Platform Engineering team into a high-scale, autonomous unit that sets the standard for engineering excellence. Define technical domain ownership for core infrastructure and scale the global team.
Who you are as a leader:
Your job is to deliver value sustainably — at a pace the team can hold indefinitely, not a sprint to burnout.
You empower, you don't assign. You give people context and autonomy, hold them accountable, and speak less so they speak more.
You build a learning team — retrospectives that turn data into action, postmortems that find root cause without blame, and deliberate work on growing each engineer and killing the bus-factor-of-one.
"The how" is non-negotiable: tested, reviewed, observable, highly available, staging-first. "Done" means in production, serving customers.
You stay hands-on enough to earn technical trust and make hard calls.
Requirements
What you bring
A strong record in Platform Engineering / DevOps, with deep hands-on Kubernetes in production.
Proven experience leading engineers: mentoring, hiring, and growing a team
Strong cloud-native and Kubernetes-native mindset: you reach for declarative, GitOps, controllers, and abstraction before bespoke scripts.
Fluency in Python, Go, and Bash sufficient to build tooling and review your team's work.
Hands-on with multi cloud at production scale (GKE, Cloud SQL, BigQuery).
Fluency in Infrastructure as Code (Terraform, KCC), Helm, and GitOps delivery (ArgoCD or similar) and opinions on doing them well at scale.
A product mindset toward platform: you treat internal engineers as customers and self-service as the goal.
A point of view on AI-assisted and spec-driven development, and how to make engineers faster with it while keeping change safe to ship.
A culture of learning from failure: blameless postmortems, real root cause, and fixing the system so the same incident can't recur.
Nice to have
Multi-cloud experience (AWS / Azure) — GCP is home, but breadth helps.
Policy-as-code (OPA/Conftest, Kyverno) and supply-chain/CI security.
SLO/error-budget practice and DORA-based delivery measurement.
Big Data or MLOps exposure (Airflow, Dagster, Ray, Kubeflow).
