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DevOps / SRE Engineer - AI Platform

šŸ‡¹šŸ‡­ Thailand

AWS

GCP

Azure

Terraform

Machine Learning

Devops

DevOps / SRE Engineer - AI Platform

from šŸ‡¹šŸ‡­ Thailand

The DevOps / SRE Engineer owns the operational substrate of an AI-native retail decisioning platform — infrastructure, CI / CD, observability, cost meter, and incident response for a system that runs production agents takingĀ real businessĀ actions. The roleĀ builds onĀ the enterprise Terraform standard, CI / CD spine, and FinOps tagging policy rather than reinventing parallel infrastructure.Ā 

Remote candidates outside of Thailand are welcome to apply.

Key Responsibilities:

    • Adopt the enterprise Terraform standard and module library for all platform infrastructure; author platform-specific modules where needed (agent runtime, vector DB, knowledge graph); run drift detection weekly.Ā 
    • Build platform-specific CI / CD pipelines on the enterprise spine — service deploys, agent deploys, eval-gate enforcement; integrate eval gates so no agent reaches production without eval pass.Ā 
    • Operate rollback orchestration with sub-15-minuteĀ recovery;Ā quarterly game days.Ā 
    • Own the platform observability stack — OpenTelemetry,Ā LangfuseĀ for LLM traces, custom dashboards for per-agent cost.Ā 
    • Implement the per-agent cost meter end-to-end — token counts, vector queries, model inference, downstream LLM Gateway costs; surface cost data to the enterprise GenAI cost dashboard.Ā 
    • Stand up the platform on-call rotation; author runbooks for every production agent and service; lead incident response with measurable corrective actions.Ā 
    • Implement platform cost-tagging policy consistent with the enterprise standard (team, domain, environment, project, agent, suite, persona); report monthly to Cost Review.Ā 
    • Drive costĀ optimisation — right-sizing, caching, model routing decisions, reservedĀ compute.Ā 
    • Bachelor's orĀ Master's degree in Computer Science, Engineering, orĀ a relatedĀ discipline.Ā 
    • 5+ years SRE / DevOps with production ownership.Ā 
    • Terraform at scale — modules, state, drift, environment promotion.Ā 
    • CI / CD for data + ML / AI services (GitLab CI / CD or comparable).Ā 
    • Cloud platform (Azure preferred; AWS / GCP transferable).Ā 
    • Observability — OpenTelemetry,Ā LangfuseĀ (or comparable LLM traces), custom dashboards.Ā 
    • FinOps — tagging policies, attribution,Ā optimisation.Ā 
    • Incident response — on-call, post-mortems, runbook authorship.Ā 

Preferred Qualifications

  • AI / agent platform SRE experience; cost-meter / chargeback systems built orĀ operated.Ā 
  • Multi-cloud production experience; open-source contributions toĀ IaCĀ / observability tooling.Ā 
  • AI / ML / agent system observability instrumentation (LLM cost, agent cost, eval scores).Ā 
  • Vendor certifications such asĀ HashiCorpĀ Terraform Associate / Professional, Azure Solutions Architect Associate, or Databricks Data Engineer Professional.Ā 
by @maxrusakovic