AI Data Engineer

Kyndryl

. Build secure, AI-ready data pipelines and retrieval architectures .

Posted 8/2/2026full-timeBangalore • 🇮🇳 IndiaMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Expertise in building secure, AI-ready data pipelines and retrieval architectures, with a strong focus on integrating operational data and designing advanced semantic search strategies. Proficient in managing data lineage, access controls, and delivering performance evaluation reports for AI applications.

Highest-signal resume keywords

Data EngineeringGenAI SupportKnowledge GraphsPython ProgrammingSQL Expertise

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data Pipeline DevelopmentETL/ELT ProcessesEmbeddingsHybrid SearchRe-RankingVector DatabasesMetadata TaggingData NormalizationAccess Control EnforcementRetrieval Performance Evaluation

Tools & Technologies

ServiceNowSharePointConfluenceGitMonitoring Tools

Industry Keywords

AI RetrievalSemantic Data ProductsData LineageAuditabilitySensitive Data Handling

Tech Stack

Tools & technologies

ETLPythonServiceNowSQL

About the role

Key responsibilities & impact

Build secure, AI-ready data pipelines and retrieval architectures
Ingest, normalize, and enrich operational data
Design advanced semantic search and metadata tagging strategies
Construct knowledge graphs and relationship maps
Enforce access controls and retention policies for AI retrieval
Maintain data dictionaries and evidence logs for audits
Build retrieval APIs for AI agents
Measure retrieval precision and response freshness

Requirements

What you’ll need

5+ years in data engineering or platform development
2+ years supporting GenAI, RAG, search, or semantic data products
Proven ability to connect enterprise data sources
Strong background in embeddings, hybrid search, re-ranking, knowledge graphs, and vector databases
Hands-on familiarity with GenAI stacks and orchestration frameworks
Expertise in Python, SQL, ETL/ELT pipelines
Practical experience integrating operational data from ServiceNow, SharePoint, Confluence, Git, and monitoring tools.
Deep understanding of enterprise data lineage, access controls, auditability, and sensitive data handling for AI usage.
Demonstrated ability to deliver AI-ready pipelines, metadata/knowledge models, vector configurations, and retrieval performance evaluation reports.

Benefits

Comp & perks

Flexible, supportive environment
Be Well programs supporting financial, mental, physical, and social health
Dynamic, hybrid-friendly culture
Access to cutting-edge learning opportunities
Coaching and hands-on experiences