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AI Products Manager

Ooredoo Qatar · Doha

Senior 🇬🇧 English
Python PyTorch TensorFlow Hugging Face Transformers Pinecone Weaviate Azure AI Search Azure OpenAI Service Azure AI Studio AWS Bedrock Google Vertex AI REST API Docker Kubernetes CI/CD Git LangGraph AutoGen CrewAI Microsoft Semantic Kernel MLflow Kubeflow CRM integration Speech-to-text Text-to-speech Multi-modal AI

Job description

About the role

The AI Products Manager is the lead builder inside Ooredoo's AI Hub, turning architectural designs and product specifications into production‑ready AI systems. You will work across the full AI engineering stack, from model training to LLM‑powered applications and agentic workflows, ensuring seamless integration with Ooredoo's enterprise platform.

Key responsibilities

  • Convert AI architecture blueprints into deployed, reliable AI solutions.
  • Train, fine‑tune, and operationalise ML and LLM models.
  • Design and implement prompt‑engineered RAG pipelines, embedding models and vector‑database solutions.
  • Build and orchestrate agent‑to‑agent (A2A) workflows using multi‑agent frameworks.
  • Integrate AI services with Ooredoo's BSS/OSS and CRM platforms via APIs or event‑driven architectures.
  • Maintain performance, reliability and continuous improvement of AI systems in production.
  • Collaborate closely with the AI Solutions Architect, providing implementation feedback.

Required profile

  • Minimum 10 years of experience in AI/ML product development.
  • Bachelor’s degree in Computer Science, Engineering or a related field.
  • Proven track record delivering end‑to‑end AI solutions in a telecom or enterprise environment.

Required skills

  • Python programming.
  • Deep‑learning frameworks: PyTorch or TensorFlow.
  • Hugging Face Transformers, LangChain.
  • Vector databases: Pinecone, Weaviate, Azure AI Search.
  • Cloud AI services: Azure OpenAI, Azure AI Studio, AWS Bedrock, Google Vertex AI.
  • REST API design, Docker, Kubernetes, CI/CD pipelines, Git.
  • Agentic AI frameworks: LangGraph, AutoGen, CrewAI, Microsoft Semantic Kernel.
  • MLOps tools: MLflow, Azure ML Pipelines, Kubeflow.
  • Experience with BSS/OSS or CRM integration patterns.
  • Speech‑to‑text, text‑to‑speech, or multi‑modal AI for voice‑enabled self‑service.

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Published 1 month ago

Expires 1 week from now

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Ooredoo Qatar

Doha