Senior DevOps Engineer

Your Roles and Responsibilities:

Cloud infrastructure (primary)

• Design, build and operate our GCP footprint: GKE, Artifact Registry, Cloud SQL (Postgres), Cloud Storage, Memorystore (Redis), Vertex AI, Cloud Monitoring/Logging, Cloud DNS
• Own network and perimeter design: VPC architecture, Private Service Connect, Cloud NAT, Cloud Armor, private connectivity to customer systems
• Own secrets, keys and identity: Secret Manager, Workload Identity, IAM design and least-privilege service accounts, KMS, certificate lifecycle
• Run R&D on platform services we haven't used yet — evaluate the GCP service, identify the Azure and AWS equivalents, and produce a recommendation with a working proof of concept, not a slide
• Manage cloud cost: attribution by product and environment, budget alerts, rightsizing, commitment planning Deployment into environments (a core reason this role exists)
• Make deploying our products into a new environment a repeatable, documented, low-drama exercise — both customer-VPC and Astreya-hosted models
• Own the deployment artefacts: Helm charts, namespace and pod topology, environment configuration, migration and rollback paths
• Work directly with customer infrastructure and security teams during onboarding — answer their architecture and security questions, adapt to their constraints, and get us to production
• Produce and maintain the evidence infrastructure security reviews and audits ask for: architecture diagrams, data flow, access controls, encryption posture, audit logging, retention

DevOps and platform engineering

• Own CI/CD across products: build pipelines, artefact promotion, environment strategy, source control branching strategies across multiple release cadences
• Write automation and internal tooling for provisioning and operating infrastructure — infrastructure as code (Terraform) as the default, scripts and services where it isn't
• Build the observability layer: metrics, logs, traces, alerting, dashboards and SLOs that let us find problems before customers do
• Improve scalability, reliability, capacity and performance of the platform, including the infrastructure serving AI/LLM workloads
• Harden the platform: image scanning, dependency and vulnerability management, network policy, secrets hygiene, patching

Leadership and process

• Lead and mentor DevOps and infrastructure engineers; set standards and review their work
• Work with product owners and engineering leads to understand requirements, surface infrastructure bottlenecks early, and propose resolutions
• Own incident response for platform issues and produce root cause analyses for outages that are honest about cause and specific about prevention
• Design and implement improvements to existing support processes and tooling; introduce innovations and follow through on execution, not just proposal
• Document decisions, runbooks and resolution history so the next person doesn't rediscover them
• Other duties as required. This list is not a comprehensive inventory of all responsibilities assigned to this position

Required Qualifications/Skills:

• Bachelor's degree from a four-year college or university and 8+ years' related experience and/or training; or an equivalent combination of education and experience
• Deep, hands-on Google Cloud experience — has designed and run production workloads on GCP, not just passed a certification
• Strong Kubernetes experience in production: GKE preferred, including networking, ingress, autoscaling, resource management and debugging failures under load
• Infrastructure as code at a professional standard — Terraform, module design, state management, review discipline
• Strong scripting and coding ability (Python, Go, Bash or equivalent) and enough software development experience to work inside application repositories, not just around them
• Practical cloud networking and security depth: VPC design, private connectivity, IAM, secrets management, TLS
• CI/CD ownership across multiple products and release trains, with source control branching strategies
• Monitoring, alerting and incident management experience, including writing the RCA afterwards
• Experience with open-source tooling in large distributed systems
• Good communication skills — can hold a technical conversation with a customer's security team and a working conversation with a developer on the same day
• Ability to pick up unfamiliar technology quickly and carry several threads at once

Preferred Qualifications

• Working Azure knowledge (AKS, Key Vault, Entra ID, VNet) and the ability to translate a GCP design onto it; AWS exposure a bonus
• Experience deploying a product into customer-controlled cloud environments as a vendor
• Experience supporting AI/ML workloads in production — Vertex AI, model endpoints, GPU scheduling, inference cost control
• Exposure to SOC 2, ISO 27001 or comparable audits from the infrastructure side
• Experience integrating with enterprise ITSM platforms (ServiceNow) and the connectivity that requires
• Prior experience as a first or early infrastructure hire on a product team
• Relevant certification (Google Professional Cloud Architect, Professional Cloud DevOps Engineer, CKA)