25 days ago
Gurgaon, IndiaStaff+
Responsibilities
- Design and develop generative AI solutions using LLMs, RAG, Graph RAG, AI agents, Agentic AI, and LangGraph for telecom operations and service assurance.
- Architect AI-powered applications for autonomous networks, intelligent operations, self-healing, self-optimization, and predictive network management.
- Build and maintain network digital twins for telecom network simulation, analysis, optimization, and capacity planning.
- Design knowledge graphs and ontologies for network intelligence, service dependency mapping, root-cause analysis, and operational insights.
- Apply Graph Neural Networks and advanced AI/ML techniques to network topology analysis, anomaly detection, fault prediction, and service impact assessment.
- Develop AIOps, network automation, incident correlation, event management, service assurance, and closed-loop operations solutions.
- Build scalable cloud-native AI platforms with Python and Azure, AWS, or GCP.
- Develop APIs and orchestration frameworks integrating AI models with telecom network management platforms.
- Integrate AI capabilities with OSS/BSS systems and telecom domains including RAN, core networks, transport networks, and IP/MPLS infrastructure.
- Lead requirements gathering, architecture design, development, deployment, testing, production rollout, proof-of-concepts, technology evaluations, and innovation initiatives.
- Establish practices for AI governance, model lifecycle management, observability, security, and responsible AI.
- Provide technical leadership, mentor engineering teams, and contribute to AI strategy and organizational capability development.
Requirements
- Experience designing and delivering AI-powered telecom and network transformation solutions is required by the role scope.
- Ability to work with generative AI, LLMs, RAG, Graph RAG, AI agents, Agentic AI, LangGraph, digital twins, knowledge graphs, ontologies, AIOps, and Graph Neural Networks.
- Ability to architect cloud-native AI platforms using Python and Azure, AWS, or GCP.
- Knowledge of telecom networks, including RAN, core networks, transport networks, IP/MPLS infrastructure, OSS/BSS, network management, and service assurance.
- Experience developing APIs, orchestration frameworks, and integrations between AI models and telecom network platforms.
- Ability to lead architecture discussions, proof-of-concepts, technology evaluations, and end-to-end solution delivery.
- Knowledge of AI governance, model lifecycle management, observability, security, and responsible AI implementation.
- Ability to provide technical leadership, mentor engineering teams, and collaborate with network architects, data engineers, product owners, and operations teams.
Benefits
- Opportunity to lead AI, generative AI, and autonomous network transformation programs for global telecom customers.
- Work with LLMs, Agentic AI, digital twins, knowledge graphs, AIOps, OpenAI, Azure OpenAI, AWS Bedrock, Gemini, and Vertex AI.
- Collaboration with telecom, cloud, and AI experts on complex network and operational challenges.
- Opportunities for continuous learning, certifications, and career growth in emerging AI and telecom technologies.
Tech Stack
Categories
About Capgemini
Capgemini is a global IT services and consulting firm that delivers strategy, cloud, AI, software engineering, and managed services to large enterprises and public-sector clients. Founded in 1967 and headquartered in Paris, it is publicly traded on Euronext Paris and operates in 50+ countries. The group expanded its engineering capabilities by acquiring Altran in 2020, now operating as Capgemini Engineering.