Senior AI/ML Data Architect

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.

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.

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:

Define and enforce data governance, lineage, metadata management, and accesscontrol 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.

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.

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 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

Strong telecom data and operations knowledge

Ability to translate complex technical designs into business value

Excellent communication, stakeholder engagement, and leadership skills