Artificial Intelligence Architect

Role Summary : Architecting Agentic AIdriven solutions that enable Telecom Autonomous Networks. The architect will work at the intersection of AI systems, telecom operations, and industry standards to drive closed-loop automation for global CSPs.

Role & responsibilities

• Collaborate with Business / Practice Units, Relevant Stakeholders, and Customers to understand business goals and determine AI requirements.
• Design and develop AI architectures, frameworks, and algorithms that can support large-scale and sophisticated AI solutions, including Agentic AI systems capable of autonomous decision-making.
• Evaluate and select appropriate AI technologies, tools, and frameworks to achieve desired performance, accuracy, and scalability.
• Own the development and implementation of AI models, ensuring consistency to standard processes in machine learning, deep learning, and Agentic AI frameworks.
• Develop and maintain AI pipelines, incorporating data cleaning, pre-processing, feature engineering, model training, and validation processes.
• Lead the architecture and design of AI- and Agent-based solutions for Network Assurance, Service Assurance, Fault Management, Performance Management, Inventory, Provisioning, and Orchestration.
• Design and implement Agentic AI systems using multi-agent paradigms where agents perceive, reason, plan, act, and learn enabling closed-loop automation aligned to Autonomous Network levels
• Translate telecom operational intents (business, service, and network intents) into agent workflows, reasoning strategies and actions.
• Work deeply with Telecom data including KPIs, counters, alarms, logs, topology, configuration, traces, and tickets, and design architectures that handle scale, and real-time constraints.
• Participate in industry forums, working groups, and internal communities to shape Autonomous Network and Agentic AI direction.

Preferred candidate profile

• Expertise & Experience working as an AI Technical Lead or Architect, with working knowledge of machine learning, deep learning, Recurrent Learning, Reinforcement Learning, Generative AI, and Agentic AI techniques.
• Experience in designing and implementing large-scale AI solutions, including data ingestion, storage, processing, and deployment.
• Good understanding of cloud computing platforms & their AI services (e.g., AWS, Azure, Google Cloud) and experience in deploying AI models on cloud native platforms. 
• Experience in Architecting and deploying Telco-specific AI applications, such as network automation, service assurance, and customer analytics etc.,
• Strong grounding in AI/ML techniques relevant to telecom operations including anomaly detection, time-series analysis, causal inference, reinforcement learning, and LLM-based reasoning
• Hands-on experience in Architecting and designing Agentic AI or autonomous systems using multi-agent frameworks (e.g., LangGraph, LangChain, custom agent frameworks) applied to real operational workflows
• Deep understanding of telecom data models, KPIs, counters, alarms, and operational workflows across RAN, Core, Transport, and Services
• Experience in programming languages such as Python, Java, or C++, and familiarity with popular AI libraries
• Excellent problem-solving and analytical skills, with the ability to break down complex problems into actionable components.
• Demonstrated experience in architecting scalable AI systems in Telco environments and that proactively address performance bottlenecks.
• Strong communication and teamwork skills, with the ability to work effectively within multi-functional teams.
• Ability to stay updated with the latest advancements in AI technologies, frameworks, and platforms.
• Should have handled larger datasets on data lakes, Kafka integration.
• Familiarity with AI governance frameworks and responsible AI practices 
• Knowledge of ethical considerations and responsible AI practices is a plus.