Data Science Architect

Your Role

Your Profile

• Design and develop next-generation Generative AI solutions leveraging LLMs, RAG, Graph RAG, AI Agents, Agentic AI, and LangGraph for telecom operations, network management, and service assurance.
• Architect and implement AI-powered applications for Autonomous Networks and Intelligent Operations, enabling self-healing, self-optimization, and predictive network management.
• Build and maintain Network Digital Twins to simulate, model, analyze, and optimize telecom network behavior, performance, and capacity planning.
• Design and develop Knowledge Graphs and Ontologies to establish network intelligence, service dependency mapping, root cause analysis, and operational insights.
• Apply Graph Neural Networks (GNNs) and advanced AI/ML techniques for network topology analysis, anomaly detection, fault prediction, and service impact assessment.
• Develop AI-driven solutions for AIOps, network automation, incident correlation, event management, and closed-loop network operations.
• Create intelligent workflows and automation frameworks to enhance Service Assurance, fault management, performance monitoring, and operational efficiency.
• Collaborate with OSS/BSS teams to integrate AI capabilities across telecom business and operational support systems.
• Design and implement solutions across telecom domains including RAN, Core Networks, Transport Networks, and IP/MPLS infrastructure.
• Build scalable cloud-native AI platforms using Python and cloud technologies such as Azure, AWS, or GCP.
• Develop APIs, microservices, and orchestration frameworks for integrating AI models with telecom network management platforms.
• Drive AI architecture discussions, technology evaluations, proof-of-concepts (PoCs), and innovation initiatives within telecom transformation programs.
• Lead end-to-end solution delivery, including requirement gathering, architecture design, development, deployment, testing, and production rollout.
• Work closely with network architects, data engineers, product owners, and operations teams to define AI use cases and business outcomes.
• Establish best practices for AI governance, model lifecycle management, observability, security, and responsible AI implementation.
• Provide technical leadership, mentor engineering teams, and contribute to AI strategy and capability development within the organization.

What You'll Love About Working Here