AI / Data Solution Architect

Responsibilities: • Architect and design end-to-end data and AI solutions ensuring scalability, performance, and security; Build and design Infrastructure as Code (IaC) using Terraform for automated infrastructure provisioning. • Design and implement data pipelines on platforms like AWS, Azure, or Databricks for data ingestion, transformation, and storage. • Create AI solutions (Computer Vision, NLP, Generative AI) by leveraging modern cloud services and frameworks. • Design and implement robust data pipelines for batch and real-time data processing; Apply Medallion Architecture, Change Data Capture (CDC), Data Lake, and Data Mesh principles. • Build large-scale data ingestion, transformation, and ETL pipelines on platforms like AWS Glue, Azure Data Factory, Databricks. • Optimize data models for high-performance query execution and downstream consumption; Enable seamless data accessibility and consumption through Data APIs or Data Products. • Implement and manage Data Governance solutions using tools like AWS DataZone, Unity Catalog, or Azure Purview. • Ensure Data Catalog, Business Glossary, Data Lineage, and Role-based Access Control (RBAC) are effectively managed. • Establish robust data policies around security, privacy, compliance, and data accessibility; Support data governance frameworks in compliance with industry regulations (e.g., GDPR, HIPAA). • Design and develop Data Warehouses with Dimension & Fact Modeling. • Ensure high performance and scalability of data models in platforms like Snowflake, Databricks, or AWS Redshift. • Architect and deploy MLOps pipelines for model training, validation, inferencing, and monitoring. • Design and build scalable AI solutions with expertise in: Model Training & Validation; Model Inferencing; API layer exposure for models; Model Monitoring and Feedback Loops; Service Catalog for ML models. • Strong knowledge of frameworks like TensorFlow, XGBoost, Hugging Face, and LangChain. • Implement GenAI (Generative AI) solutions and Large Language Models (LLMs) for custom model development and fine-tuning. • Design and deploy AI solutions in the areas of: Computer Vision – Image classification, object detection, OCR, image segmentation; Natural Language Processing (NLP) – Text generation, summarization, sentiment analysis, named entity recognition (NER). • Work with tools like LangChain, HuggingFace, OpenAI API, Bedrock, Azure OpenAI for AI model development. • Design and deploy CI/CD pipelines for data, machine learning, and AI models; Automate infrastructure provisioning using Terraform, CloudFormation, Azure Bicep, etc. • Ensure scalable and secure deployment of data and AI solutions.; Enable monitoring and model drift detection in AI/ML pipelines. • Strong knowledge of IICS (Informatica Intelligent Cloud Services) for ETL/ELT pipelines. • Experience with Snowflake for high-performance Data Warehousing. • Familiarity with Generative AI models (LLMs, HuggingFace, OpenAI API). • Understanding of model fine-tuning, embedding models, and Prompt Engineering. • Experience with LangChain, HuggingFace, Bedrock, OpenAI, Azure OpenAI for AI development. Requirements: • 12+ years of experience in Data Architecture, Data Engineering, and AI Solutioning. • Strong experience with Infrastructure as Code (IaC) using Terraform or similar tools. • Proficiency in building data pipelines in AWS, Azure, or Databricks environments. • Hands-on expertise in MLOps pipelines, Model deployment, and Model Monitoring. • Experience in developing Computer Vision and NLP solutions. • Strong understanding of Data Governance frameworks like AWS DataZone, Unity Catalog, or Azure Purview. • Hands-on experience with Data Warehouse (Dimension/Fact Modelling). • Working knowledge of Generative AI (GenAI), Large Language Models (LLMs), and Model Fine-tuning; Consulting experience a must Show more Show less

12+ years of experience in Data Architecture, Data Engineering, and AI Solutioning. Strong experience with Infrastructure as Code (IaC) using Terraform or similar tools. Proficiency in building data pipelines in AWS, Azure, or Databricks environments. Hands-on expertise in MLOps pipelines, Model deployment, and Model Monitoring. Experience in developing Computer Vision and NLP solutions. Strong understanding of Data Governance frameworks like AWS DataZone, Unity Catalog, or Azure Purview. Hands-on experience with Data Warehouse (Dimension/Fact Modelling). Working knowledge of Generative AI (GenAI), Large Language Models (LLMs), and Model Fine-tuning; Consulting experience a must.

Architect and design end-to-end data and AI solutions ensuring scalability, performance, and security; Build and design Infrastructure as Code (IaC) using Terraform for automated infrastructure provisioning. Design and implement data pipelines on platforms like AWS, Azure, or Databricks for data ingestion, transformation, and storage. Create AI solutions (Computer Vision, NLP, Generative AI) by leveraging modern cloud services and frameworks. Design and implement robust data pipelines for batch and real-time data processing; Apply Medallion Architecture, Change Data Capture (CDC), Data Lake, and Data Mesh principles. Build large-scale data ingestion, transformation, and ETL pipelines on platforms like AWS Glue, Azure Data Factory, Databricks. Optimize data models for high-performance query execution and downstream consumption; Enable seamless data accessibility and consumption through Data APIs or Data Products. Implement and manage Data Governance solutions using tools like AWS DataZone, Unity Catalog, or Azure Purview. Ensure Data Catalog, Business Glossary, Data Lineage, and Role-based Access Control (RBAC) are effectively managed. Establish robust data policies around security, privacy, compliance, and data accessibility; Support data governance frameworks in compliance with industry regulations (e.g., GDPR, HIPAA). Design and develop Data Warehouses with Dimension & Fact Modeling. Ensure high performance and scalability of data models in platforms like Snowflake, Databricks, or AWS Redshift. Architect and deploy MLOps pipelines for model training, validation, inferencing, and monitoring. Design and build scalable AI solutions with expertise in: Model Training & Validation; Model Inferencing; API layer exposure for models; Model Monitoring and Feedback Loops; Service Catalog for ML models. Strong knowledge of frameworks like TensorFlow, XGBoost, Hugging Face, and LangChain. Implement GenAI (Generative AI) solutions and Large Language Models (LLMs) for custom model development and fine-tuning. Design and deploy AI solutions in the areas of: Computer Vision – Image classification, object detection, OCR, image segmentation; Natural Language Processing (NLP) – Text generation, summarization, sentiment analysis, named entity recognition (NER). Work with tools like LangChain, HuggingFace, OpenAI API, Bedrock, Azure OpenAI for AI model development. Design and deploy CI/CD pipelines for data, machine learning, and AI models; Automate infrastructure provisioning using Terraform, CloudFormation, Azure Bicep, etc. Ensure scalable and secure deployment of data and AI solutions.; Enable monitoring and model drift detection in AI/ML pipelines. Strong knowledge of IICS (Informatica Intelligent Cloud Services) for ETL/ELT pipelines. Experience with Snowflake for high-performance Data Warehousing. Familiarity with Generative AI models (LLMs, HuggingFace, OpenAI API). Understanding of model fine-tuning, embedding models, and Prompt Engineering. Experience with LangChain, HuggingFace, Bedrock, OpenAI, Azure OpenAI for AI development.