AIML Cloud Engineer AWS, Azure

Key Skills

AWS

Azure

CDK

CDKTF

Terraform

TypeScript

Python

Boto3 CI/CD

CodePipeline

AI/ML Services

Azure Data Platform

SageMaker Studio

Docker

Containers

Cloud Architecture

Cloud Infrastructure Architecture & Engineering

Work collaboratively with a team of Cloud Engineers to design and build robust scalable AWS infrastructure.

Partner with development teams to understand technical requirements and provision AWS services to support AI and Machine Learning workloads.

Architect lowlatency scalable systems ensuring performance reliability and operational excellence.

AI/ML Platform Support

Work with Product Managers to develop tooling and platforms that support experimentation environments ML model training workflows and production ML operations and deployments

Support MLOps practices through automation monitoring and infrastructure optimization.

Data & DevOps Engineering

Provision and maintain end-to-end data solutions using DevOps methodologies with AWS CDK CDKTF or Terraform.

Design and implement data pipelines including data ingestion processing and orchestration.

Reliability Disaster Recovery & Platform Operations

Design and maintain DR strategies backup policies and resilient architectures for critical workloads.

Engineering Excellence & Collaboration

Promote high engineering standards including consistent coding practices and rigorous code reviews.

Identify troubleshoot and resolve complex technical challenges across environments.

Prioritize and manage multiple projects to ensure timely delivery and alignment with organizational goals.

MustHave Skills & Qualifications

Cloud Platforms

Development & Automation Skills

Proficiency in at least one programming language: TypeScript or Python (including Boto3 for AWS automation)

Experience building CI/CD pipelines using tools such as: AWS CodePipeline Azure DevOps and GitHub Actions

Hands-on experience with CDK (AWS) or Terraform / CDKTF for Infrastructure as Code.

AI/ML & Azure Data Platform Expertise

Experience with AWS SageMaker Studio for ML workloads.

Containerization

Hands-on experience deploying and managing containerized applications using Docker.

Problem-Solving & Communication

Excellent decision-making consulting and technical support skills.

Strong experience deploying and managing Azure AI & Data services including:

Microsoft OpenAI

Azure AI Search

Azure AI Translator

Azure Machine Learning

Azure Data Factory

Azure Databricks

Azure Data Lake Storage

Power BI

Azure SQL Database

Required Skills:

Overview: We are seeking an experienced Cloud Engineer with strong expertise in AWS and Azure platforms AI/ML infrastructure DevOps practices and modern Infrastructure as Code frameworks. The ideal candidate will excel at designing scalable cloud architectures supporting data/ML workloads and automating deployments using CDK CDKTF or Terraform. Key Skills AWS Azure CDK CDKTF Terraform TypeScript Python Boto3 CI/CD CodePipeline AI/ML Services Azure Data Platform SageMaker Studio Docker Containers Cloud Architecture Cloud Infrastructure Architecture & Engineering Work collaboratively with a team of Cloud Engineers to design and build robust scalable AWS infrastructure. Partner with development teams to understand technical requirements and provision AWS services to support AI and Machine Learning workloads. Architect low latency scalable systems ensuring performance reliability and operational excellence. AI/ML Platform Support Work with Product Managers to develop tooling and platforms that support experimentation environments ML model training workflows and production ML operations and deployments Support MLOps practices through automation monitoring and infrastructure optimization. Data & DevOps Engineering Provision and maintain end-to-end data solutions using DevOps methodologies with AWS CDK CDKTF or Terraform. Design and implement data pipelines including data ingestion processing and orchestration. Implement capacity planning frameworks to ensure scalability and resource efficiency. Reliability Disaster Recovery & Platform Operations Design and maintain DR strategies backup policies and resilient architectures for critical workloads. Ensure platforms adhere to best practices for security performance and reliability. Engineering Excellence & Collaboration Promote high engineering standards including consistent coding practices and rigorous code reviews. Identify troubleshoot and resolve complex technical challenges across environments. Prioritize and manage multiple projects to ensure timely delivery and alignment with organizational goals. Must Have Skills & Qualifications Cloud Platforms Hands-on experience designing deploying and managing Azure cloud infrastructure. Strong experience provisioning AWS services and supporting multi-cloud environments. Development & Automation Skills Proficiency in at least one programming language: TypeScript or Python (including Boto3 for AWS automation) Experience building CI/CD pipelines using tools such as: AWS CodePipeline Azure DevOps and GitHub Actions Hands-on experience with CDK (AWS) or Terraform / CDKTF for Infrastructure as Code. AI/ML & Azure Data Platform Expertise Experience with AWS SageMaker Studio for ML workloads. Containerization Hands-on experience deploying and managing containerized applications using Docker. Problem-Solving & Communication Excellent decision-making consulting and technical support skills. Strong collaboration skills with internal and external teams. Strong experience deploying and managing Azure AI & Data services including: Microsoft OpenAI Azure AI Search Azure AI Translator Azure Machine Learning Azure Data Factory Azure Databricks Azure Data Lake Storage Power BI Azure SQL Database