AI Architect with Telecommunications

. AI/ML Solution Development for Telecom

. Design and implement AI/ML models for telecom use cases such as

1. Network anomaly detection
2. Fault prediction and root cause analysis
3. Traffic forecasting and capacity optimization
4. Predictive maintenance

. Work with structured and unstructured network data (KPIs, alarms, logs, performance metrics)

2. Telecom Domain Integration (OSS / RAN / Core)

1. Work closely with OSS platforms (e.g., NetAct), SON, and network management systems
2. Understand RAN/Core network architecture and integrate AI models into operational workflows
3. Translate network-level challenges into data-driven solutions

3. AI-Driven Automation & AIOps

. Implement AIOps capabilities for: Incident prediction and reduction Automated alert correlation Intelligent ticketing and prioritization
. Enable closed-loop automation using AI insights

4. Data Engineering & Pipeline Development

. Build and manage data pipelines for ingesting telecom data from multiple sources
. Work with big data technologies (e.g., Spark, Kafka, Hadoop – preferred)
. Ensure data quality, preprocessing, and feature engineering

5. AI Integration in DevOps / CI-CD

. Integrate AI models into CI/CD pipelines for continuous deployment and monitoring
. Enable model lifecycle management (MLOps)
. Work with containerized environments (Docker, Kubernetes)

6. Stakeholder Collaboration

. Collaborate with: Network operations teams OSS/NetAct engineers DevOps and platform teams
. Participate in use case identification, solution design, and implementation discussions

7. Governance, Security & Compliance

. Ensure compliance with data privacy, security, and telecom regulations
. Implement best practices for model governance and explainability