Role Overview :

As an AI-Expert, you will be the primary strategist and driver for transforming traditional network operations into an AI-augmented, autonomous ecosystem.

You will be responsible for the entire lifecycle of AI integration - from initial solutioning and architectural design to leading development and managing the ongoing operations of production-grade AI platforms.

Your objective is to leverage Machine Learning and Generative AI to automate troubleshooting, optimize network planning, and assist in real-time issue resolution across the enterprise.

Key Responsibilities :

Solutioning & Strategic Design :

- AI Roadmap & Strategy : Define and drive the vision for AI-integrated network management, focusing on faster incident triage and reduced manual intervention.

- SME Collaboration : Work closely with Network SMEs to translate natural-language troubleshooting playbooks and "tribal knowledge" into structured, deterministic AI logic.

- Workflow Orchestration : Design complex, multi-stage diagnostic and operational pipelines that move the organization toward a "lights-out" NOC (Network Operations Center).

- Predictive Frameworks : Architect systems for anomaly detection, predictive maintenance, and capacity forecasting to identify risks before they impact service.

- Governance & Ethics : Ensure all AI solutions maintain high standards of auditability, security, and deterministic reliability.

Development & Implementation Leadership :

- Advanced AI Integration : Lead the implementation of LLM-based solutions, including Retrieval-Augmented Generation (RAG) for knowledge management and automated resolution procedures.

- Data Science & Engineering : Oversee the normalization and ingestion of massive telemetry streams from diverse hardware vendors into unified, actionable data models.

- Automation & Self-Healing : Oversee the creation of "closed-loop" systems that can automatically execute remedial actions - such as failovers or re-routing - based on AI-driven insights.

- Stakeholder Tools : Manage the development of intuitive dashboards and interfaces that deliver AI-driven Network insights to NOC engineers, customer support, and senior management.

Operational Management & Optimization :

- Continuous Learning Loops : Establish mechanisms to capture human feedback and real-world results to continuously refine AI models and diagnostic rules.

- Performance Monitoring : Own key platform metrics, including diagnostic accuracy, false positive rates, and total system latency.

- Scale & Resilience : Manage the operational health of AI services, ensuring high availability, graceful degradation during data gaps, and a clear path for future scaling.

Required Core Competencies :

- Artificial Intelligence : Deep expertise in ML, LLMs (Generative AI), RAG architectures, and vector search technologies.

- Systems Architecture : Proven ability to design asynchronous, request-response pipelines and high-performance data ingestion services.

- Network Domain : Broad understanding of network telemetry, topology, and the lifecycle of network incident management is good to have.

- Operational Leadership : Experience managing production AI systems with a focus on auditability and deterministic outcomes.