Enterprise Data and AI Architect to drive the Data and AI initiatives from ideation design and deployment.
Key Responsibilities: AI/ML Strategy: Design the architectural framework for scaling Artificial Intelligence and Machine Learning models. This includes building pipelines for LLMs Generative AI and predictive analytics. AWS Cloud Governance: Act as the lead architect for AWS environments ensuring best practices in VPC design serverless architectures (Lambda) and cost optimization (FinOps). Data Mesh & Analytics: Overhaul legacy data silos into a modern Data Lakehouse or Data Mesh architecture to support real-time business intelligence and data-driven decision-making. AI Ethics & Security: Establish guardrails for data privacy in AI models and ensure AWS security protocols (IAM GuardDuty) are strictly followed.
Required Skills: Cloud Platform: Proficiency in AWS Ecosystem (S3 SageMaker Redshift Glue Bedrock and EKS). Data Frameworks: Experience with Snowflake Databricks or Apache Spark for large-scale data processing. AI Frameworks: Familiarity with PyTorch TensorFlow or LangChain for integrating AI into enterprise workflows. Automation: Strong background in IaC (Infrastructure as Code) using Terraform or AWS CloudFormation.
Preferred Qualifications: AWS Certifications: Highly preferred (e.g. AWS Certified Solutions Architect Professional or AWS Certified Data Engineer). Analytics Background: Proven track record of designing platforms that handle Petabyte-scale data and complex ETL/ELT processes. AI Integration: Experience moving AI projects from Proof of Concept (PoC) to full-scale enterprise production.
Enterprise Data and AI Architect to drive the Data and AI initiatives from ideation design and deployment. Key Responsibilities: AI/ML Strategy: Design the architectural framework for scaling Artificial Intelligence and Machine Learning models. This includes building pipelines for LLMs Genera...
Enterprise Data and AI Architect to drive the Data and AI initiatives from ideation design and deployment.
Key Responsibilities: AI/ML Strategy: Design the architectural framework for scaling Artificial Intelligence and Machine Learning models. This includes building pipelines for LLMs Generative AI and predictive analytics. AWS Cloud Governance: Act as the lead architect for AWS environments ensuring best practices in VPC design serverless architectures (Lambda) and cost optimization (FinOps). Data Mesh & Analytics: Overhaul legacy data silos into a modern Data Lakehouse or Data Mesh architecture to support real-time business intelligence and data-driven decision-making. AI Ethics & Security: Establish guardrails for data privacy in AI models and ensure AWS security protocols (IAM GuardDuty) are strictly followed.
Required Skills: Cloud Platform: Proficiency in AWS Ecosystem (S3 SageMaker Redshift Glue Bedrock and EKS). Data Frameworks: Experience with Snowflake Databricks or Apache Spark for large-scale data processing. AI Frameworks: Familiarity with PyTorch TensorFlow or LangChain for integrating AI into enterprise workflows. Automation: Strong background in IaC (Infrastructure as Code) using Terraform or AWS CloudFormation.
Preferred Qualifications: AWS Certifications: Highly preferred (e.g. AWS Certified Solutions Architect Professional or AWS Certified Data Engineer). Analytics Background: Proven track record of designing platforms that handle Petabyte-scale data and complex ETL/ELT processes. AI Integration: Experience moving AI projects from Proof of Concept (PoC) to full-scale enterprise production.
View more
View less