Devops Engineer

Description

ZyG is revolutionizing eCommerce with the first Agentic Operating System for eCom scale.

This end-to-end platform helps product inventors and entrepreneurs turn their products into successful Direct-to-Consumer businesses, addressing the three key challenges of eCom scale: poor product bets, lack of scale infrastructure, and the need for often-complex financing.

With a connected system of AI Agents built on a unified data infrastructure, the OS analyzes scale-market fit, replaces the fragmented tools, agencies, and manual workflows that typically power eCom growth, and offers the financing needed for DTC scale.

The Role

We're looking for a DevOps Engineer to join a fast-moving, AI-native engineering team.

This is not a traditional ops role.

A large share of our code is written and shipped by AI agents. The platform underneath them has to keep up.

You'll be expected to help our dev teams ship, debug, and monitor fast, using AI wherever it fits.

This is a ground-floor seat on a startup with serious growth ambitions.

If you want to build the platform that lets a team of humans and agents ship at machine speed, this is your role

What you'll do

- Run CI/CD end to end: GitHub Actions, Bazel builds, and Argo CD deploys. Make them faster, greener, and safe for agents to trigger unattended
- Build and maintain the infrastructure as code behind the platform on GCP with Terragrunt and OpenTofu: GKE, VPC networking, IAM, Secret Manager, Cloud SQL
- Run the data platform: Cloud Composer (Airflow), dbt, and the BigQuery layer the business reports on. Keep pipelines on schedule, cheap, and trustworthy
- Keep production observable: Datadog and Grafana, alerts people trust, error tracking that points at the real fault
- Put AI to work on ops: extend the agent-driven alert triage, wire Claude Code into pipelines, automate the toil you'd otherwise do by hand
- Work with backend and data engineers to make services and pipelines resilient, observable, and easy to deploy

Requirements

- Minimum 4 years of hands-on DevOps/SRE experience
- Kubernetes in production: you've deployed it, upgraded it, and debugged networking on it
- GCP: GKE, Cloud SQL, BigQuery, Secret Manager, IAM, VPC networking
- Infrastructure as code with Terragrunt and OpenTofu (Terraform experience counts)
- CI/CD depth: good knowledge of GitHub Actions, and GitOps on Kubernetes with Argo CD, Flux, or equivalent
- DataOps: Airflow, dbt, and a warehouse like BigQuery. You've operated pipelines in production, not only written them
- Monitoring and alerting with Datadog, Grafana, or similar
- Comfortable scripting and reading code in Go, Python, or TypeScript
- A pulse on what's actually breaking in production right now
- Someone who thrives with responsibility, moves fast, and wants to build something big

Nice to have

- Bazel: you've managed the build of a big monorepo
- Crossplane
- Istio or another service mesh in production
- Temporal or another durable workflow engine
- Helm chart authoring and Kubernetes operators
- Supply-chain security tooling: Trivy, gitleaks, SBOM