Accountabilities

Own the target architecture of the managed cloud platform on Google Cloud Platform (GCP), including dedicated customer environments, clusters, networks, databases, queues, infrastructure templates, and regional deployment strategy.

Define the architectural roadmap and guide the platform's evolution from Beta to General Availability, balancing customer isolation, reliability, scalability, and infrastructure costs.

Write and maintain technical specifications, design documents, RFCs, and Architecture Decision Records (ADRs), clearly explaining technical trade-offs and implementation choices.

Define Service Level Objectives (SLOs) and error budgets for services and service tiers, using them to guide engineering priorities.

Lead technical delivery across a team of three, including yourself, by breaking down architectural plans into actionable work, assigning responsibilities, reviewing implementation, and removing blockers.

Establish engineering standards for Terraform modules, Helm charts, infrastructure configuration, and GitOps practices.

Automate the complete customer-instance lifecycle, including provisioning, upgrades, scaling, backups, migrations, and decommissioning.

Own the deployment and release strategy using ArgoCD and GitHub Actions, implementing progressive rollouts, rollback mechanisms, and safe upgrades across customer environments.

Build and maintain an end-to-end observability stack covering metrics, logs, traces, and alerting to identify and resolve issues proactively.

Lead on-call operations and incident response, including rotation planning, runbooks, blameless postmortems, and implementation of corrective actions.

Plan infrastructure capacity for variable workloads and ensure autoscaling strategies remain effective and reliable.

Drive cloud cost optimization through FinOps practices, including customer-level cost visibility, resource right-sizing, committed-use discounts, and appropriate use of spot instances.

Strengthen platform security in collaboration with the security engineer, covering network policies, workload identity, secrets management, and audit trails in support of SOC 2 expectations.

Collaborate with core platform engineering to identify product improvements that simplify cloud operations and improve platform reliability.

Lead the technical milestones for the first six months, including architecture assessment, GA specifications and SLOs, automated customer provisioning, observability coverage, and safe upgrade capabilities.

Requirements

At least 8 years of experience in Site Reliability Engineering, platform engineering, or infrastructure engineering, including a minimum of 2 years leading technical direction for a team or platform.

Deep, production-grade Kubernetes expertise, including experience operating clusters at scale and managing upgrades, configuration drift, networking, and resource allocation.

Strong hands-on experience with Google Cloud Platform, particularly GKE, IAM, VPC networking, private clusters, load balancing, and managed data services.

Expert-level Terraform skills, including the design of reusable module structures and state management approaches that support multiple identical customer environments.

Proven ability to define technical architecture, write detailed specifications, evaluate trade-offs, and translate designs into executable engineering plans.

Demonstrated experience coordinating technical delivery, reviewing implementation, and guiding a small engineering team.

Strong operational experience with on-call rotations, incident management, postmortems, and implementing lasting reliability improvements.

Background operating SaaS products for paying customers, with direct responsibility for production reliability and meaningful SLOs.

Fluent English and the ability to work independently and collaboratively in a fully remote international environment.

Pragmatic engineering judgment, with the ability to choose straightforward, maintainable solutions and clearly explain technical decisions.

Nice to have: Experience operating workloads that execute untrusted or user-defined code, including sandboxing, gVisor, or node-pool isolation.

How Jobgether works

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

#LI-CL1