Data Architect, Generative AI & Data Platform

As the Principal Architect, Generative AI & Data Platforms, you will play a strategic role in architecting and operationalizing the end-to-end data ecosystem that fuels Generative AI, Machine Learning (ML), and advanced analytics. Your focus will be on building a robust, scalable, and compliant platform utilizing modern cloud and Gen AI techniques such as RAG to transform raw data into a reliable asset for data scientists, analysts, and business intelligence users. **Core Responsibilities:** - Define and lead the technical roadmap for data architecture, optimizing data storage, indexing, and retrieval patterns for Gen AI and RAG pipelines. - Design and manage highly available, performant, and cost-optimized data solutions across major cloud platforms (AWS, Azure, GCP). - Create advanced data models and semantic layers tailored to accelerate ML model training, feature engineering, and real-time analytical queries. - Implement strict Data Governance, lineage, and privacy frameworks to ensure ethical and secure use of data in all AI/ML initiatives. - Collaborate with MLOps and Data Science teams to streamline data flow from ingestion to model training, versioning, and deployment. - Architect secure, high-speed data ingestion and egress mechanisms to integrate internal and external data sources. - Act as the subject matter expert on data architecture and effectively communicate technical vision to stakeholders. **Required Skills & Qualifications:** - Proven experience in designing and implementing scalable Gen AI/ML data architectures, Vector Databases, and RAG patterns. - Expertise in data modeling and Big Data processing tools such as Spark, Databricks, and data warehousing. - Deep hands-on experience architecting data solutions on major cloud platforms like AWS, Azure, or GCP. - Strong understanding of the Data Engineering lifecycle, real-time streaming, and API integration techniques. - Exceptional communication, stakeholder management, and collaboration skills. - Bachelor's degree in Computer Science, Engineering, or a related field; advanced degree preferred.,