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Job Description
Enterprise Architect (Data, AI & AWS) Torrance, CA (Hybrid) Job description: Enterprise Architect (AI & Cloud Transformation) 1. Key Responsibilities (The "Strong Wants")
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. 2.
Preferred Technical Stack 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. 3.
Skills & 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.