DevOps Engineer

Job Overview

We are looking for a DevOps / Platform Engineer to own and evolve the infrastructure that keeps our AI agent evaluation platform reliable, observable, secure, and fast to ship to. You'll work closely with backend, ML, and frontend engineers to make deploying and operating services boring, repeatable, and safe.

Key Responsibilities

• Cloud infrastructure as code: Own and extend our Terraform estate across multiple GCP environments, including GKE clusters, Cloud SQL, networking, buckets, and IAM.


• Kubernetes & containers: Manage workloads on GKE, maintain Dockerfiles and Helm-style application configs for backend services, and tune autoscaling, resource limits, and pod disruption budgets.


• Maintain and improve CI/CD pipelines: PR checks, Terraform prechecks, image builds and pushes, auto-deploy, and DB-migration labelling/gating.


• Data & messaging infrastructure: Operate Postgres, Redis, and Celery-based async workers; manage Alembic migrations, queue health, and backpressure for long-running simulation jobs.


• Observability: Own our monitoring stack — Grafana dashboards, ClickHouse, Langfuse (LLM tracing), and Celery queue metrics.


• Security & secrets: Manage secret distribution, least-privilege IAM, and remediation tracking.


• Cost & reliability: Keep an eye on cloud and LLM-proxy spend, right-size resources, and improve resilience of the simulation and evaluation pipelines.

Required Qualifications

Experience:

• 3+ years in DevOps / SRE / Platform Engineering, or strong backend experience with heavy infra ownership.


• Solid hands-on Terraform and cloud experience (GCP preferred).


• Production Kubernetes experience: deployments, services, autoscaling, debugging pods, rollouts/rollbacks.


• Strong Docker fundamentals and comfort writing/optimising Dockerfiles.


• CI/CD pipeline design and maintenance (GitHub Actions).


• Comfortable scripting and reading code in Python and/or Bash.


• Operational experience with relational databases and managed database services.


• Reliability mindset: monitoring, alerting, incident response, and writing runbooks.

Bonus points for:

• Experience operating Celery / distributed task queues and Redis at scale.


• Familiarity with LLM/AI infrastructure.


• Observability tooling depth (Grafana, Prometheus, ClickHouse, OpenTelemetry, Langfuse).


• Security/compliance experience (IAM hardening, secret management, vulnerability remediation).


• Cost-optimisation experience for cloud + third-party API spend.


• Experience supporting a monorepo with multiple language ecosystems.

Benefits

Competitive salary, training budget, private insurance, top-tier tech gear, and the chance to work with a stellar crew.