MLOps Engineer (Relocation to Serbia)

Posted 2026-05-06
Remote, USA Full-time Immediate Start

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.


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 within Europe (preferred: Croatia, Poland, Portugal, Serbia).

  • European working hours.

  • Occasionally available for meetings up to 10:00 AM PST (US overlap).

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