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Data AI Architect

Infosys
Bengaluru, India
13-15 Years
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Job Description

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 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

More Info

Job Type:
Permanent Job
Industry:
Other
Function:
Software Engineering
Employment Type:
Full time

About Company

Infosys

Job ID: 147183447

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Last Updated: 11-05-2026 07:47:46 PM
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