Sr AI /ML Data Architect (Telecom Domain)

Role: Sr AI /ML Data Architect (Telecom Domain)
Location Baskin Ridge ,NJ (Hybrid)
Duration: Long term contarct

Seeking a highly experienced Senior AI/ML Data Architect with deep expertise in Telecom OSS/BSS systems, Network Operations, AI/ML, GenAI, Data Platforms, and Cloud Architecture. The ideal candidate will lead enterprise-scale AI-driven transformation initiatives focused on network intelligence, service assurance, predictive operations, automation, customer analytics, and OSS modernization.

This role will define AI-enabled data architecture strategy, design scalable data platforms, and drive next-generation telecom solutions leveraging AI/ML, GenAI, real-time analytics, and cloud-native technologies.

Key Responsibilities
AI/ML & Data Architecture
Define enterprise AI/ML and data architecture roadmap for telecom OSS/BSS ecosystems.
Design scalable batch and real-time data platforms supporting network, service, customer, and operational analytics.
Architect AI-powered solutions for:
Predictive Maintenance
Fault Prediction
Root Cause Analysis (RCA)
Capacity Forecasting
Customer Experience Analytics
Churn Prediction
Network Optimization
Service Assurance
Design MLOps platforms supporting model development, deployment, monitoring, and governance.
Telecom OSS/BSS Architecture

Architect integrations across:
Inventory Management
Provisioning
Activation
Service Fulfillment
Service Assurance
Workforce Management
Performance Management
Fault Management
Drive OSS modernization initiatives and migration from legacy systems to cloud-native platforms.
Align architecture with TM Forum standards including SID, eTOM, ODA, and Open APIs.

GenAI & Advanced Analytics
Design and implement Generative AI solutions for telecom operations.
Build AI copilots for NOC/SOC operations.
Implement RAG-based architectures using LLMs for telecom knowledge management and operational automation.
Drive AI governance, responsible AI, explainability, and model monitoring frameworks.

Cloud & Data Engineering
Architect cloud-native data ecosystems on AWS, Azure, or GCP.
Design enterprise Data Lakes, Lakehouse, and Data Mesh architectures.
Implement streaming architectures using Kafka, Spark Streaming, Flink, Kinesis, or Pub/Sub.
Drive data quality, metadata management, lineage, cataloging, and governance initiatives.

Leadership
Provide architectural leadership across distributed engineering and data science teams.
Interface with client executives, business stakeholders, and telecom operations leadership.
Lead solution workshops, architecture reviews, PoCs, and AI transformation programs.

Required Skills
Telecom Domain
OSS/BSS Architecture
Service Fulfillment
Service Assurance
Inventory Management
Network Operations Center (NOC)
4G/5G Networks
Fiber Networks
SD-WAN
TM Forum Standards (SID, eTOM, ODA, Open APIs)
AI/ML
Machine Learning
Deep Learning
Generative AI
LLMs
NLP
Predictive Analytics
Time-Series Forecasting
MLOps
Responsible AI
Data Technologies
Snowflake
Databricks
Hadoop
Spark
Kafka
Flink
Delta Lake
Data Lakehouse
Data Modeling
ETL/ELT
Cloud
AWS
Azure
GCP
Kubernetes
Docker
Terraform
Programming
Python
PySpark
SQL
Scala
Java
Visualization
Tableau
Power BI
Looker
Grafana

TOGAF Certification.
Cloud Architect Certification (AWS/Azure/GCP).
Master's Degree in Computer Science, Data Science, Telecommunications, or related field.