Drive the future of AI-powered telecom and autonomous network transformation. This role focuses on designing and implementing scalable data, analytics, and AI solutions across telecom networks. You'll combine deep telecom expertise with advanced data engineering, AI/ML, and cloud technologies to enable intelligent operations and network optimization.

As a Telco AI & Data Engineering Architect, you will architect and deliver end-to-end telecom data and AI platforms. These platforms will support network analytics, automation, AIOps, and autonomous network initiatives. You will collaborate closely with CSP customers, network architects, data scientists, and business stakeholders to drive digital transformation across various network environments.

Architect and deliver comprehensive telecom data, analytics, and AI solutions for network intelligence and autonomous operations. Design robust data foundations to enable closed-loop automation, self-optimizing networks, and intent-based operations. Lead telecom network and data transformation programs spanning RAN, Core (2G/3G/4G/5G), Transport, and OSS/BSS domains. Develop and implement large-scale data lakes, data warehouses, and analytics platforms tailored for telecom environments. Build and optimize data pipelines for processing diverse telecom data sources, including CDRs, xDRs, PM/FM counters, telemetry, inventory, and network topology. Create AI/ML solutions for crucial areas like capacity forecasting, anomaly detection, network optimization, predictive analytics, and customer insights. Architect both streaming and batch processing platforms utilizing modern data engineering technologies. Design and deploy AI-powered use cases to support AIOps, Service Assurance, Network Analytics, and Autonomous Networks. Lead greenfield implementations and modernize existing legacy telecom data platforms. Drive pre-sales activities, including solution architecture, technical proposal development, effort estimation, and customer presentations. Collaborate with network teams, data scientists, cloud architects, and business stakeholders to define strategic transformation roadmaps. Oversee end-to-end delivery, from architecture and development through deployment, migration, and operational handover. Establish and enforce best practices for data governance, quality management, security, and platform observability. Mentor engineering teams and actively contribute to telecom AI and data strategy initiatives.

Mandatory Skills: - Strong experience in Telecom Networks, including RAN, Core (2G/3G/4G/5G), Transport, IP Networks, BSC/BTS, EPC, and 5GC. - Expertise in Data Engineering, Big Data, and Analytics Architecture. - Hands-on experience with Apache Spark, Kafka, Airflow, Hadoop, dbt, SQL, and NoSQL technologies. - Strong knowledge of cloud data platforms like AWS, Azure, or GCP. - Experience developing AI/ML solutions using Python, PySpark, Scikit-Learn, TensorFlow, or PyTorch. - Understanding of Autonomous Networks, Closed-Loop Automation, AIOps, and SON concepts. - Proven experience building telecom analytics platforms and processing large-scale network datasets. - Solid grasp of Data Governance, Data Quality, ETL/ELT, and Data Lifecycle Management. - Experience with APIs, Automation Frameworks, and Infrastructure Automation. - Demonstrated success in telecom transformation programs and customer-facing solution architecture.

Preferred Skills: - Familiarity with TM Forum ODA/eTOM Frameworks. - Experience with MLOps and Model Lifecycle Management. - Knowledge of Telecom Network Automation tools (Cisco NSO, Crosswork, SD-WAN). - Proficiency in Power BI, Tableau, and Advanced Analytics. - Experience with Ansible, Terraform, YANG/NETCONF. - Exposure to AI-driven Network Operations and Service Assurance. - Relevant certifications (e.g., Azure Data Engineer/AI, AWS Data Analytics/Machine Learning, Google Professional Data Engineer, Databricks, TM Forum, Snowflake).