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Data AI Architect

Infosys Limited -
Bengaluru, Karnataka

Apply Now

Job details

Qualifications

CI/CD
MATLAB
Power BI
Azure
Law
Big data
Spark
Git
AWS
Quality assurance
Embedded software
Continuous integration
GitHub
Agile
Apache
Kafka
Metadata
AI
Jenkins
Analytics

Full job description

Key Responsibilities:

Key Responsibilities
Data Architecture for AI
Architect AI data foundations including ingestion transformation enrichment and serving layers
Design data architectures supporting RAG embeddings feature stores and training data pipelines
Define standards for data quality lineage versioning and governance for AI workloads
Ensure data platforms support scalability performance and low latency AI use cases
Data Quality Assurance
Architect data validation and testing frameworks for AI and analytics systems
Enable automated validation for data correctness drift bias and completeness
Define test strategies for data migration data transformation and AI readiness
Collaborate with QE teams to embed data assurance into pipelines and platforms
Platform Integration
Integrate data platforms with AI services and analytics tools
Define secure access patterns for data used in training inference and evaluation
Enable observability for data pipelines and AI data consumption
Guide teams on best practices for AI enabled BI and data driven systems
Core Platforms Frameworks Tooling
LLM and foundation model platforms e
g
AWS Bedrock Azure OpenAI Vertex AI
Agentic AI and orchestration frameworks LangChain LangGraph CrewAI AutoGen Google ADK or equivalent
CI CD and MLOps tooling for AI pipelines GitHub Actions Azure DevOps Jenkins
Data ingestion and processing platforms Spark Kafka cloud native ETL ELT frameworks
Data quality and validation frameworks Great Expectations Amazon Deequ custom reconciliation frameworks
Feature stores and embedding pipelines Feast embedding generation pipelines vector databases
Data drift bias and consistency monitoring tools Evidently statistical data quality monitors
Metadata lineage and governance platforms DataHub Apache Atlas cloud data catalogs
AI enabled analytics and Generative BI platforms Power BI with Copilot semantic layers NLQ enabled BI
Cloud native data platforms and storage object storage distributed query engines data lakehouses
Client Orientation Leadership
Partner with product and engineering teams to identify Data for AI opportunities and shape roadmaps
Support client workshops RFPs and solution presentations
Mentor engineers on AI ML Gen AI best practices and emerging technologies
Translate complex AI concepts into business friendly narratives

Technical Requirements:

Must Have Qualifications
13 years of experience in software engineering with 3 years in AI with strong architecture ownership
Strong expertise in data engineering data quality and data governance
Experience supporting AI use cases such as RAG feature engineering and model training
Proficiency with data platforms cloud services and distributed data systems
Solid understanding of QE practices related to data validation and testing
Good to Have Skills
Experience with Generative BI or AI assisted analytics
Knowledge of metadata management lineage tools and data observability
Exposure to AI ethics and bias in data sets
Cloud data certifications

Preferred Skills:

Technology->AI-Generative AI->Generative AI - Basic->retrieval augmented generation (rag),Technology->Data Engineering->Databricks,Technology->Data Engineering->Palantir Foundry,Technology->Data Management->Data Architecture->Data Architecture - Data Modeling,Technology->Embedded Software->Matlab,Technology->Agile Testing->Agile Testing - ALL->CD/CI,Technology->Integration->Confluent Kafka,Technology->Big Data - Data Processing->Spark

Apply Now

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