Data Architect, Generative AI & Data Platform

Role Summary :

The Principal Architect, Generative AI & Data Platforms is a strategic role responsible for architecting and operationalizing the end-to-end data ecosystem that powers Generative AI, Machine Learning (ML), and advanced analytics . This role focuses on building a robust, scalable, and compliant platform—leveraging modern cloud and Gen AI techniques (like RAG)—to transform raw data into a reliable, secure asset for data scientists, analysts, and business intelligence users.

Experience : 12 - 18 years

Location : Chennai

Core Responsibilities

• Gen AI / ML & Data Platform Strategy : Define and lead the technical roadmap for data architecture, specifically optimizing data storage, indexing (e.g., Vector Stores), and retrieval patterns for Gen AI and RAG (Retrieval Augmented Generation) pipelines.
• Cloud & Big Data Architecture : Design and manage highly available, performant, and cost-optimized data solutions across major cloud platforms (AWS, Azure, GCP). Utilize Big Data technologies (Spark, Databricks, Snowflake, Kafka) for processing petabyte-scale data volumes.
• Data Modeling for Intelligence : Create advanced data models (e.g., Dimensional, Data Vault) and semantic layers specifically tailored to accelerate ML model training, feature engineering, and real-time analytical queries.
• Data Governance & Trust : Implement strict Data Governance, lineage, and privacy frameworks, ensuring the ethical and secure use of data in all AI / ML initiatives. Establish robust Data Quality and auditing mechanisms.
• MLOps & Deployment Alignment : Directly collaborate with MLOps and Data Science teams to streamline the flow of data from ingestion to model training, versioning, and high-volume inference deployment.
• API & Data Integration : Architect secure, high-speed data ingestion and egress mechanisms, including Real-Time Data Streams and Microservices-based APIs, to integrate diverse internal and external data sources.
• Leadership & Technical Evangelism : Act as the subject matter expert on data architecture across the organization. Effectively communicate complex technical vision and trade-offs to c-suite and non-technical stakeholders

✅ Required Skills & Qualifications