AI Products Manager

About the role

The Manager AI Products leads the AI Hub in turning architectural designs and product specifications into production‑deployed AI systems. The role covers the full AI engineering stack, from model training to enterprise integration.

Key responsibilities

• Develop and deploy AI solutions by training and fine‑tuning ML models and building LLM‑powered applications.
• Design and implement agentic workflows and multi‑agent orchestration across platforms.
• Integrate AI systems with Ooredoo’s enterprise platform ecosystem via APIs or event‑driven architecture.
• Maintain reliability, performance, and continuous improvement of deployed AI services.
• Collaborate closely with the AI Solutions Architect, providing implementation feedback on architecture blueprints.

Required profile

• Minimum 10 years of experience in AI/ML product development.
• Strong proficiency in Python and its AI/ML ecosystem.
• Hands‑on experience building LLM applications, prompt engineering, RAG pipelines, and using vector databases.
• Experience with major cloud AI services (Azure OpenAI, Azure AI Studio, AWS Bedrock, Google Vertex AI).
• Solid software engineering fundamentals: REST API design, Docker/Kubernetes, CI/CD pipelines, Git workflows.
• Proven ability to integrate AI solutions with enterprise platforms and telecom BSS/OSS or CRM systems.
• Experience designing and orchestrating agent‑to‑agent (A2A) solutions using frameworks such as LangGraph, AutoGen, CrewAI, or Microsoft Semantic Kernel.
• Familiarity with MLOps tooling (MLflow, Azure ML Pipelines, Kubeflow) and multimodal AI (speech‑to‑text, text‑to‑speech).

Required skills

• Python
• PyTorch or TensorFlow
• Hugging Face Transformers
• LangChain
• Pinecone, Weaviate, Azure AI Search
• Azure OpenAI Service, Azure AI Studio, AWS Bedrock, Google Vertex AI
• REST API design
• Docker, Kubernetes
• CI/CD pipelines, Git
• API and event‑driven integration
• LangGraph, AutoGen, CrewAI, Microsoft Semantic Kernel
• MLflow, Azure ML Pipelines, Kubeflow
• BSS/OSS systems, CRM integration patterns
• Speech‑to‑text, text‑to‑speech, multimodal AI