AI Data Architect

Kyndryl; Bengaluru; On-site; INR 4,000,000 - 7,000,000; Full time

Benefits offered by this job

Flexible, hybrid-friendly culture

Be Well programs

Certifications with Microsoft/Google/A

Coaching and hands-on experiences

Job summary

Kyndryl is seeking an accomplished Senior Data Architect to define and lead the target-state AI data architecture across all lifecycle stages. You will design ingestion, enrichment, and structuring mechanisms for enterprise data to support AI agents and multi-agent workflows.

You will enforce strict data governance including privacy, access control, traceability, and compliance with enterprise standards while shaping data products and lakehouses for AI readiness in a hybrid, dynamic environment.

Qualifications

• 10+ years in enterprise data/platform architecture.
• 3+ years specifically building GenAI, RAG, and AI agent data models.
• Expertise in context management, grounding, chunking, and hybrid search across vector engines and major LLMs.
• Deep experience in canonical and semantic data modeling, data products, lakehouses, and modern data platforms.
• Proven track record with ServiceNow, CMDB models, ticket workflows, SLA analytics, and transforming operational IT assets into AI-ready data products.
• Strong capability in designing Zero Trust data access, data mesh concepts, lineage tracking, privacy controls, and audit frameworks for enterprise compliance.
• Skilled in establishing evaluation datasets, drift detection, retrieval performance metrics, and agent contract schemas to eliminate hallucinations.
• Ability to facilitate workshops, drive data discovery under ambiguity, run architecture reviews, and align multi-disciplinary engineering and business teams

Responsibilities

• Design blueprints and canonical models for ingesting, enriching, and serving operational enterprise data to AI agents.
• Architect governed APIs, retrieval services, context packages, and structured output schemas for multi-agent workflows and Agent Builder platforms.
• Collaborate with engineering and security teams to ensure compliant, auditable data access and governance across environments.
• Lead architecture reviews and workshops to drive data discovery and align cross-functional teams.
• Translate business needs into scalable data products and data platforms that support GenAI workflows.

Skills

Data architecture

GenAI & RAG

Context management

Canonical data modeling

Zero Trust data access

Privacy controls

Workshop facilitation

Architecture reviews

Tools

ServiceNow

CMDB models

Ticket workflows

SLA analytics

Job description

Role Overview

The ideal candidate will define and lead the target-state AI data architecture across all lifecycle stages. In this role, you will architect mechanisms to ingest, prepare, and structure complex enterprise data sources for seamless AI agent consumption.

What You Will Do

Design blueprints and canonical models for ingesting, enriching, and serving operational enterprise data to AI agents. Architect governed APIs, retrieval services, context packages, and structured output schemas for multi-agent workflows and Agent Builder platforms.

Why It Might Be a Fit

You will enforce strict data governance, ensuring all data accessed by AI agents remains highly accurate, permission-aware, traceable, auditable, and compliant with customer privacy and data boundary standards.

Requirements

• 10+ years in enterprise data/platform architecture
• 3+ years specifically building GenAI, RAG, and AI agent data models
• Expertise in context management, grounding, chunking, and hybrid search across vector engines and major LLMs
• Deep experience in canonical and semantic data modeling, data products, lakehouses, and modern data platforms
• Proven track record with ServiceNow, CMDB models, ticket workflows, SLA analytics, and transforming operational IT assets into AI-ready data products
• Strong capability in designing Zero Trust data access, data mesh concepts, lineage tracking, privacy controls, and audit frameworks for enterprise compliance
• Skilled in establishing evaluation datasets, drift detection, retrieval performance metrics, and agent contract schemas to eliminate hallucinations
• Ability to facilitate workshops, drive data discovery under ambiguity, run architecture reviews, and align multi-disciplinary engineering and business teams

Benefits

• Flexible, supportive environment
• Prioritized well-being
• Potential to thrive and contribute to our culture of empathy and shared success
• Be Well programs to support financial, mental, physical, and social health
• Dynamic, hybrid-friendly culture
• Impactful work that powers the systems our customers rely on every day
• Cutting-edge learning opportunities
• Access to certifications with Microsoft, Google, and Amazon
• Coaching and hands-on experiences