Overview

We are looking for an experienced AI Architect to lead the AI direction and oversee the design and implementation of a scalable AWS-based Data and MLOps Platform for the Non-Profit Assist AI Program. The project scope covers onboarding, architecture validation, and the implementation of an MLOps foundation on AWS SageMaker.
Project Overview:

Responsibilities:
  • Define and lead the AI architecture vision, aligning technical decisions with the organization’s long-term data and AI strategy.
  • Refine the overall AWS architecture across Data, Infrastructure, and Security layers.
  • Set up and manage UAT and Production environments.
  • Establish automated pipelines using AWS SageMaker Projects and Pipelines.
  • Integrate GitHub Actions for continuous integration and delivery across all environments.
  • Expose ML models through secure and scalable APIs using Lambda and API Gateway.
  • Build monitoring, logging, and alerting systems through CloudWatch and SageMaker Model Monitor.
  • Produce architecture diagrams, configuration guidelines, and handover documentation.
Required Qualifications:
  • 5+ years of experience in Data or AI architecture, with strong expertise in AWS.
  • Proven track record in designing and implementing production-grade MLOps platforms on SageMaker.
  • Deep understanding of AWS services: S3, Step Functions, Lambda, API Gateway, IAM, CloudWatch, CloudFormation, Terraform.
  • Experience building data workflows that integrate with external sources (e.g., Snowflake).
  • Hands-on CI/CD experience using GitHub Actions or equivalent.
  • Proficiency in Python for ML pipeline development and automation.
  • Solid understanding of data security, compliance, and governance best practices.
Note:

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