Data Architect AWS and AI/ML EXP
Listed on 2026-06-05
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IT/Tech
AI Engineer, Data Engineer
Position:
Data Architect with AWS and AI/ML EXP Hire Type:
Full Time
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 (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.
Required Skills: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.
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.
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