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Makro PRO Linkedin · Posted 13d ago

DevOps / SRE Engineer - AI Platform

Nawamin

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Indexed description

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 taking real business actions. The role builds on the enterprise Terraform standard, CI / CD spine, and FinOps tagging policy rather than reinventing parallel infrastructure.

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.
  • 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.
  • Operate rollback orchestration with sub-15-minute recovery; quarterly game days.
  • Own the platform observability stack — OpenTelemetry, Langfuse for LLM traces, custom dashboards for per-agent cost.
  • 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.
  • Stand up the platform on-call rotation; author runbooks for every production agent and service; lead incident response with measurable corrective actions.
  • Implement platform cost-tagging policy consistent with the enterprise standard (team, domain, environment, project, agent, suite, persona); report monthly to Cost Review.
  • Drive cost optimisation — right-sizing, caching, model routing decisions, reserved compute.

Requirements

  • Bachelor's or Master's degree in Computer Science, Engineering, or a related discipline.
  • 5+ years SRE / DevOps with production ownership.
  • Terraform at scale — modules, state, drift, environment promotion.
  • CI / CD for data + ML / AI services (GitLab CI / CD or comparable).
  • Cloud platform (Azure preferred; AWS / GCP transferable).
  • Observability — OpenTelemetry, Langfuse (or comparable LLM traces), custom dashboards.
  • FinOps — tagging policies, attribution, optimisation.
  • Incident response — on-call, post-mortems, runbook authorship.

Preferred Qualifications

  • AI / agent platform SRE experience; cost-meter / chargeback systems built or operated.
  • Multi-cloud production experience; open-source contributions to IaC / observability tooling.
  • AI / ML / agent system observability instrumentation (LLM cost, agent cost, eval scores).
  • Vendor certifications such as HashiCorp Terraform Associate / Professional, Azure Solutions Architect Associate, or Databricks Data Engineer Professional.
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