Data Architect, Generative AI

1 hour ago

Chennai, India Saaki Argus and Averil Consulting Full time

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 yearsLocation: Chennai💡 Core ResponsibilitiesGen 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 & QualificationsTechnical Expertise: Proven experience designing and implementing scalable Gen AI/ML data architectures, Vector Databases, and RAG patterns. Expert-level proficiency in data modeling (conceptual, logical, physical) and Big Data processing tools (Spark, Databricks, DWH).Cloud Mastery: Deep hands-on experience architecting data solutions on at least one major cloud platform (AWS, Azure, or GCP), including native data services (e.g., AWS S3/Glue, Azure Data Lake/ADF, GCP BigQuery/Dataproc).Data Lifecycle: Strong understanding of the complete Data Engineering lifecycle (ELT/ETL, CI/CD, and monitoring), real-time streaming, and API integration techniques.Soft Skills: Exceptional communication, stakeholder management, and cross-functional collaboration skills. Ability to mentor and lead technical teams.Education: Bachelor's degree in Computer Science, Engineering, or a related quantitative field. An advanced degree is strongly preferred.

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