AI​/ML + Data Architect

Enterprise Data and AI Architect to drive the Data and AI initiatives from ideation , design and deployment.

• 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 (Fin Ops).
• 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, Guard Duty) are strictly followed.

• Cloud Platform:
  Proficiency in AWS Ecosystem (S3, Sage Maker, Redshift, Glue, Bedrock, and EKS).
• Data Frameworks:
  Experience with Snowflake, Databricks, or Apache Spark for large-scale data processing.
• AI Frameworks:
  Familiarity with PyTorch, Tensor Flow, or Lang Chain for integrating AI into enterprise workflows.
• Automation:
  Strong background in IaC (Infrastructure as Code) using Terraform or AWS Cloud Formation.

• 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.