Akvelon

MLOps Engineer (Relocation to Serbia)

Akvelon

Kazakhstan Remote DevOps 2 days ago via Himalayas
mlops-engineering ai-platform-engineering platform-engineering devops-engineering ml-infrastructure-engineering mlops kubernetes terraform python ci-cd azure kubeflow

Job details

Company
Akvelon
Location
Kazakhstan
Remote
Yes
Field
DevOps
Source
via Himalayas
Posted April 24, 2026
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About this role

This engagement is focused on building an internal AI platform that enables developers to ship AI-powered services efficiently. Scope includes model connectivity, prompt testing and evaluation, monitoring/observability, and the underlying AI infrastructure layer.

The objective is to improve DevEx and reduce time-to-market for AI features.

Location: Serbia (relocation support available), Croatia, Poland, Portugal

Tasks

  • Build and operate the AI platform infrastructure enabling developers to ship LLM-based services faster.
  • Implement and maintain Kubernetes-based runtime environments (incl. AKS) for AI workloads.
  • Manage infrastructure as code with Terraform (modules, environments, CI/CD automation).
  • Support LLM workflows: RAG, agents, prompt experimentation, evaluations, and deployment patterns.
  • Integrate and operate tooling such as Azure AI Foundry, LiteLLM, Langfuse, MLflow.
  • Orchestrate pipelines using Kubeflow Pipelines and/or Argo Workflows (build, deploy, evaluate).
  • Improve platform reliability and observability (monitoring, logging, tracing, cost/perf signals).
  • Collaborate closely with developers to streamline DX (APIs, templates, docs, golden paths, automation).

Requirements

  • Strong hands-on experience with Kubernetes in production (preferably AKS).
  • Solid Terraform expertise (IaC best practices, multi-env setups).
  • Practical experience supporting ML/LLM workloads in a platform or DevOps/MLOps context.
  • Proficiency in Python for automation, scripting, and supporting APIs/evaluation tooling.
  • Understanding of CI/CD, release processes, and production-grade operations.
  • Ability to work under tight timelines and deliver pragmatically.

Nice to Have

  • Experience building internal developer platforms or “paved roads” for engineering teams.
  • Familiarity with LLM evaluation frameworks, prompt testing workflows, and LLM observability.
  • Exposure to RAG architectures, vector databases, and agentic patterns.
  • Experience with Kubeflow, Argo, and ML lifecycle tooling.

Engagement Type

  • Long-term B2B contract.

Team

  • You will join a team of 5, with 3 AI Platform Engineers being added.

Location / Timezone

  • Remote work from Croatia, Poland, Portugal, and Serbia.
  • European working hours.
  • Occasionally available for meetings up to 10:00 AM PST (US overlap).

Originally posted on Himalayas

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