Infrastructure Engineer

Posted 11 Days Ago
Hiring Remotely in United Kingdom
Remote
Senior level
Information Technology
Building Spatial AI for commerce. Tracking every product in every store realtime using passive associate Smartbadges.
The Role
Build and operate highly available GCP infrastructure for international engineering teams and customer deployments. Manage Kubernetes clusters, automate deployments, develop internal infrastructure tooling, and oversee monitoring, alerting, maintenance, and incident response. Establish async handoffs for continuous global coverage across EU, US, and APAC teams. The role also supports agentic AI and LLM workflows, with opportunities to work on data pipelines and stream-processing architectures.
Summary Generated by Built In

At Augmodo, we are expanding our global footprint and building a follow-the-sun engineering model. Currently, our core infrastructure team is based in the US Bay Area. As our customer base and engineering cohorts grow internationally—particularly across Europe and Australia—we need an infrastructure engineer stationed in the EU/EMEA time zone.

In this role, you will be the anchor for our European engineering cohort, drive system reliability, and serve as the infrastructure lead during EU business hours. You’ll balance active incident response and system maintenance with long-term infrastructure building.

Key Responsibilities
  • Serve as the primary infrastructure contact during EU working hours, extending coverage to support cross-regional needs in APAC (AUS) and EMEA.

  • Build, scale, and optimize infrastructure dedicated to supporting our growing EMEA teams and regional customer deployments.

  • Proactively manage system health, monitoring, alerting, and incident response for GCP-based workloads to maintain high availability.

  • Automate deployments, manage Kubernetes clusters, and build internal tooling that empowers developers to ship code safely and fast.

  • Establish effective async workflows and handoff protocols with other infrastructure teams to ensure seamless 24/7 continuity.

Core Qualifications
  • 5+ years of experience as a software engineer in a production environment.

  • Bachelor's degree in computer science, engineering, or math.

  • 3+ years of hands-on experience running and scaling workloads in Google Cloud Platform (GCP).

  • 3+ years of experience managing production Kubernetes clusters (GKE experience is a big plus).

  • Proficiency in Python and Go for building infrastructure automation, APIs, and operational tooling.

  • Demonstrated experience with Infrastructure as Code (Terraform/Pulumi), CI/CD pipelines, and observability tools (Prometheus, Grafana, Datadog, etc.).

  • High degree of self-direction and clear async communication skills, with experience thriving in distributed team environments.

  • Familiarity with hosting, serving, or orchestrating agentic AI systems and LLM workflows.

Nice-to-Have
  • Experience building and scaling modern data pipelines or stream-processing architectures.

  • Experience working with early-stage technical companies

Working Hours & Overlap
  • This role is based in the London (BST/GMT) or Central European (CET/CEST) time zones.

  • Expect a schedule that provides comfortable overlap with the US Bay Area team for syncs/handoffs (typically early afternoon EU / morning PT), while providing critical coverage during EU hours and the start of the APAC business day.

Skills Required

  • 5+ years of experience as a software engineer in a production environment
  • Bachelor's degree in computer science, engineering, or mathematics
  • 3+ years of hands-on experience running and scaling workloads in Google Cloud Platform
  • 3+ years of experience managing production Kubernetes clusters
  • Proficiency in Python and Go
  • Experience with Infrastructure as Code using Terraform or Pulumi
  • Experience with CI/CD pipelines
  • Experience with observability tools such as Prometheus, Grafana, or Datadog
  • Self-direction and clear asynchronous communication skills in distributed team environments
  • Familiarity with hosting, serving, or orchestrating agentic AI systems and LLM workflows
  • Experience building and scaling modern data pipelines or stream-processing architectures
  • Experience working with early-stage technical companies
  • Availability to work in the London or Central European time zones
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The Company
HQ: Seattle, Washington
33 Employees

What We Do

Spatial AI for commerce

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