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Senior LLMOps / AI Platform Engineer

IC Markets Global
Dubai, UAE
Full-time
Mid
Onsite
Discovered 2 days ago
awsdockerfastapigithub-actionshelmkubernetes

Full Job Posting

Key Responsibilities

  • Deploy and operate self-hosted LLMs using vLLM, SGLang, Ollama.
  • Optimize LLM inference for latency, throughput, concurrency, GPU memory, KV cache, and cost.
  • Manage GPU workloads across multiple NVIDIA GPUs.
  • Deploy and maintain AI services on Kubernetes / AWS EKS using Docker and Helm.
  • Implement LLM reliability mechanisms including health checks, monitoring, automated recovery, and model restart/refresh strategies.
  • Implement observability using Langfuse/LangSmith, OpenTelemetry, Prometheus, and Grafana.
  • Deploy and optimize RAG systems, embedding models, and vector databases such as Qdrant, Milvus.
  • Support AI agents and workflows built with LangChain and LangGraph.
  • Build and maintain CI/CD pipelines for AI services and infrastructure.
  • Troubleshoot production issues across LLMs, GPUs, Kubernetes, networking, and AI applications.

Required Skills

  • Strong Python and FastAPI experience
  • vLLM, Hugging Face and self-hosted LLM deployment
  • Kubernetes, Docker, Helm and AWS
  • NVIDIA GPU inference and performance optimization
  • LangChain / LangGraph/LangSmith
  • RAG, embeddings and vector databases (Qdrant)
  • LLM observability and monitoring
  • PostgreSQL / Redis
  • GitHub Actions / CI/CD
  • Strong production troubleshooting skills

Qualifications

  • Strong Python and FastAPI experience
  • vLLM, Hugging Face and self-hosted LLM deployment
  • Kubernetes, Docker, Helm and AWS
  • NVIDIA GPU inference and performance optimization
  • LangChain / LangGraph/LangSmith
  • RAG, embeddings and vector databases (Qdrant)
  • LLM observability and monitoring
  • PostgreSQL / Redis
  • GitHub Actions / CI/CD
  • Strong production troubleshooting skills

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