AI/ML Data Architect (Telecom)

Radiant Digital; Basking Ridge (NJ); On-site; USD 160,000 - 250,000; Full time

Job summary

Radiant Digital is seeking a Senior AI/ML Data Architect to lead the design of end-to-end AI-enabled data platforms for telecom data. The role focuses on LLM-based architectures, RAG pipelines, AI agents, and scalable data solutions across OSS/BSS and network operations.

You will bridge data architecture, AI enablement, and telecom intelligence, delivering governance, security, and high-performance data systems with strong leadership and collaboration.

Qualifications

• Overall 20+ years of IT experience.
• 12+ years in data engineering, data architecture, or analytics platforms.
• 5+ years working in the Telecom domain (Network, OSS/BSS, 4G/5G).
• Proven experience delivering LLM-based and AI-driven data platforms.
• Strong expertise in LLMs, RAG architectures, and enterprise AI integration.
• Hands-on coding in Python or Java.
• Advanced SQL and data modeling skills.
• Cloud experience with enterprise-scale AI and data workloads.
• Excellent communication, stakeholder engagement, and leadership skills.

Responsibilities

• Design and implement LLM-enabled architectures, including RAG solutions using telecom data.
• Architect and govern AI agents and multi-agent systems for automation, diagnostics, decision support, and workflow orchestration.
• Enable secure integration of LLMs and agents with enterprise data platforms, APIs, and business systems.
• Define best practices for prompt engineering, model orchestration, evaluation, and feedback loops.
• Lead the design of large-scale, cloud-native data platforms capable of processing high-volume telecom data.
• Architect low-latency and batch data ecosystems handling CDRs, network telemetry, logs, KPIs, customer interactions, and documents.
• Design end-to-end data pipelines for ingestion, transformation, enrichment, feature creation, and serving layers.
• Build AI-ready pipelines optimized for LLM training, inference, agent context retrieval, and model lifecycle management.
• Ensure real-time and batch pipeline reliability using observability, data quality checks, and automated monitoring.
• Implement CI/CD-driven pipeline deployments and versioning.
• Partner with OSS, BSS, Network Engineering, IT, and Business teams to translate telecom use cases into scalable AI data solutions.
• Apply deep understanding of telecom KPIs, network layers, subscriber data, and operational workflows.
• Enable AI use cases including network anomaly detection, intelligent NOC automation, customer experience analytics, and fraud detection.

Skills

LLM architectures

RAG models

AI agents

Data pipelines

Python

Java

Data lakes/lakehouse

Telecom data

Streaming/batch data

SQL & data modeling

Cloud data platforms

Tools

CI/CD tooling

Observability tools

Job description

12+ years Data Architecture/Data Engineering

5+ years Telecom Domain

2-5 years GenAI/LLM Implementation

Hands-on Python

Built RAG Solutions

Designed AI Agents

Architected Data Lakes/Lakehouses

Worked on OSS/BSS and 4G/5G Data

Job Description ,

We are seeking a Senior AI/ML Data Architect with strong expertise in Large Language

Models (LLMs), AI agents, large-scale data systems, and end-to-end data pipeline creation,

specifically within the Telecom domain. This role is responsible for architecting AI-ready

data platforms that power intelligent automation, advanced analytics, and agent-based

decision systems across OSS/BSS, network operations, and customer engagement.

The ideal candidate will bridge data architecture, AI/ML enablement, and telecom domain

intelligence, enabling scalable, governed, and high-performance AI solutions.

Key Responsibilities,

Design and implement LLM-enabled architectures, including RAG

(Retrieval-Augmented Generation) solutions using structured and unstructured

telecom data.

Architect and govern AI agents and multi-agent systems for automation,

diagnostics, decision support, and workflow orchestration.

Enable secure integration of LLMs and agents with enterprise data platforms, APIs, and business systems.

Define best practices for prompt engineering, model orchestration, evaluation, and feedback loops.

Lead the design of large-scale, cloud-native data platforms capable of processing high-volume, high-velocity telecom data.

Architect low-latency and batch data ecosystems handling CDRs, network telemetry, logs, KPIs, customer interactions, and documents.

• Select and implement appropriate data architecture patterns such as Lakehouse, Streaming-first, and Data Mesh.

Design and oversee end-to-end data pipelines covering ingestion, transformation, enrichment, feature creation, and serving layers.

Build AI-ready pipelines optimized for LLM training, inference, agent context retrieval, and model lifecycle management.

Ensure real-time and batch pipeline reliability using observability, data quality

checks, and automated monitoring.

Implement CI/CD-driven pipeline deployments and versioning.

Telecom Domain Enablement

Partner with OSS, BSS, Network Engineering, IT, and Business teams to translate telecom use cases into scalable AI data solutions.

Apply deep understanding of telecom KPIs, network layers, subscriber data, and operational workflows.

Enable AI use cases including:

Network anomaly detection & root-cause analysis

Intelligent NOC and assurance automation

Customer experience analytics & churn prediction

Fraud detection and revenue assurance

Governance, Security & Compliance

Define and enforce data governance, lineage, metadata management, and access control for large data and AI systems.

• Ensure compliance with data privacy regulations and secure AI usage across platforms.

Establish responsible AI and LLM governance frameworks.

6. Technical Leadership

Act as a domain expert and solution authority for AI/ML data architecture.

Define architectural standards, reference models, and reusable frameworks.

Mentor engineers, architects, and data teams.

Contribute to enterprise AI and data transformation roadmaps.

Required Skills & Experience

Experience

Overall 20+ years of IT experience

12+ years in data engineering, data architecture, or analytics platforms

5+ years working in the Telecom domain (Network, OSS/BSS, 4G/5G)

Proven experience delivering LLM-based and AI-driven data platforms

Technical Skills

Strong expertise in LLMs, RAG architectures, and enterprise AI integration

Hands-on experience designing AI agents and agent orchestration frameworks

Hands on experience in developing, testing and deployment solution

Fully hands on coding experience in Python or Java

Deep knowledge of large-scale data systems (batch & streaming)

Expertise in creating robust, scalable data pipelines

• Strong understanding of ML pipelines, feature engineering, and AI lifecycle needs

Advanced SQL and data modeling skills

Cloud experience with enterprise-scale AI and data workloads

Domain & Soft Skills

Strong telecom data and operations knowledge

Ability to translate complex technical designs into business value

Excellent communication, stakeholder engagement, and leadership skills