Role - Senior Data architect with AI/ML (119757-1)
Location Baskin Ridge ,NJ
Vendor rate -$80
Work Mode Hybrid (Client)
Infosys/Verizon
Job Description,
We are seeking a Senior AI/ML Data Architect with strong expertise in Large Language Models (LLMs), AI agents, largescale data systems, and endtoend data pipeline creation, specifically within the Telecom domain. This role is responsible for architecting AIready data platforms that power intelligent automation, advanced analytics, and agentbased 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 highperformance AI solutions.
Key Responsibilities,
- LLM & AI Agent Architecture
- Design and implement LLMenabled architectures, including RAG (RetrievalAugmented Generation) solutions using structured and unstructured telecom data.
- Architect and govern AI agents and multiagent 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.
- LargeScale Data Architecture
- Lead the design of largescale, cloudnative data platforms capable of processing highvolume, highvelocity telecom data.
- Architect lowlatency and batch data ecosystems handling CDRs, network telemetry, logs, KPIs, customer interactions, and documents.
- Select and implement appropriate data architecture patterns such as Lakehouse, Streamingfirst, and Data Mesh.
- Data Pipelines & Engineering
- Design and oversee endtoend data pipelines covering ingestion, transformation, enrichment, feature creation, and serving layers.
- Build AIready pipelines optimized for LLM training, inference, agent context retrieval, and model lifecycle management.
- Ensure realtime and batch pipeline reliability using observability, data quality checks, and automated monitoring.
- Implement CI/CDdriven 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 & rootcause 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.
- 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
- 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 LLMbased and AIdriven data platforms
Technical Skills
- Strong expertise in LLMs, RAG architectures, and enterprise AI integration
- Handson experience designing AI agents and agent orchestration frameworks
- Deep knowledge of largescale 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 enterprisescale 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
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