Senior DevOps Engineer - Cloud Platform & Security (GCP)

The role

emater is a profitable multi-brand direct-to-consumer e-commerce group (four brands on Shopify) on a growth path toward $100M. The engine of that growth is an AI and automation platform — production LLM agents, a cross-brand BigQuery data warehouse, and workflow automation — and that platform needs ground to stand on. We are hiring the engineer who builds that ground: a governed Google Cloud foundation, real cloud security, and a modern software delivery lifecycle for the whole engineering team.

This is a build role, not a ticket queue. Today, parts of the estate still run on legacy self-managed hosting and single-machine setups; access and security are managed informally; delivery practices vary by project. You will inherit a documented company — a partner-endorsed technology roadmap, a written platform architecture, and decision records — and a funded mandate to replace all of that with infrastructure the company can scale on.

What you will do

• Build the governed GCP foundation — project and environment structure, IAM with least privilege, service accounts, secret management, logging, monitoring and alerting, budgets and cost discipline. GCP (BigQuery, Cloud Run) is the company cloud; you make it governable.
• Migrate production workloads onto company cloud — including the AI agent runtime — off single-person and single-machine dependencies and legacy self-managed servers, without disrupting the live daily workflows the team depends on.
• Own cloud security — one accurate, current access map (no unknown admins), secrets handling, audit logging, network posture, backup and disaster recovery with tested restores, and incident-response basics the team can actually follow.
• Build the SDLC end to end — CI/CD on the company’s GitHub organizations, environment strategy (dev / staging / production), branch and release discipline, automated testing integration with QA, and AI-assisted code review in the pipeline. The team ships across four Shopify storefronts and internal services; you give them one disciplined way to do it.
• Stand up and operate the AI platform’s infrastructure — the containerized agent runtime, a self-hosted open-source agent memory service (Docker + PostgreSQL on GCP, with a managed Cloud SQL path), and, as the platform matures, a model gateway for per-agent cost attribution and budgets.
• Support the data platform’s operations — access, cost, and monitoring posture for the BigQuery warehouse, alongside the data engineer who owns its content.
• Document as you go — infrastructure as code as the primary documentation, plus runbooks the rest of the team can operate from.

What we are looking for

• 8+ years in DevOps / platform / infrastructure engineering, with production systems you built and operated yourself.
• Deep GCP experience — this is a must: IAM and access governance, Cloud Run (or equivalent container platforms), Secret Manager, Cloud Monitoring and Logging, cost management; BigQuery operations a strong plus.
• AWS experience as well — we run on GCP, but we want an engineer fluent in more than one cloud who chooses tools on merit.
• Cloud security depth: least-privilege design, secrets and key management, audit logging, network security, backup/DR. You treat security as an enabler designed in from day one — not a gate bolted on later.
• SDLC construction from scratch: you have built CI/CD pipelines, environment strategies, and release processes where none existed — and brought a team along with you.
• Infrastructure as code (Terraform or similar) and solid Linux administration — part of the current estate is hand-managed servers you will be retiring.
• Scripting fluency (Python and/or Bash) and comfort with Docker and containerized workloads.
• Working proficiency in English. Knowledge of Armenian is a bonus. (The engineering team is Armenian-speaking. Documentation and company leadership work in English).
• A bonus, not a requirement: exposure to LLM/AI platforms or agent infrastructure, e-commerce or Shopify context, workflow tools (n8n), Looker.

Why this role, why now

Nearly everything on emater’s technology roadmap sequences behind this role: the AI agents move to company cloud on the runtime you build, the team’s delivery discipline runs through your pipelines, and the security posture of a company heading toward $100M is the one you design. The roadmap is written, the mandate is funded, and the single points of failure you will be eliminating are named and known. Foundation work is rarely this visible, at emater it is the first thing everyone else is waiting on.