AI Cloud Architect

Overview

• We are looking for a AI Cloud Architect + developer who can design, develop, and deploy cloud-based solutions for our clients.
• You will be responsible for creating scalable, secure, and cost-effective cloud architectures that meet the business and technical requirements of the projects.
• You will also be involved in coding, testing, debugging, and troubleshooting cloud applications using various cloud services and tools.
• You will work closely with other developers, architects, and project managers to deliver high-quality cloud solutions that meet the client's expectations and deadlines.

Responsibilities

• Design and develop

  AI cloud architectures

  and applications using AWS/ Azure/Google Cloud, or other cloud platforms.
• Conduct research and feasibility analysis for GenAI use cases relevant to the customer’s business.
• Review offshore deliverables to ensure adherence to best practices and quality standards before client submission.
• Collaborate with cross-functional teams to align technical solutions with business goals.
• Confidently

  articulate AI/ML concepts

  and practices to both technical and non-technical stakeholders.
• Integrate cloud solutions with existing systems and applications using APIs, microservices, and other methods.
• Optimize cloud resources and

  costs using automation

  , monitoring, and analytics tools.
• Document and communicate cloud architectures and applications using diagrams, reports, and presentations.
• Research and

  evaluate new cloud technologies

  and trends to improve the existing cloud solutions and create new opportunities.

Qualifications

• Bachelor's degree in computer science, engineering

  , or related field.
• At least 7 years of experience in

  cloud architecture and development using AWS/Azure/Google Cloud, or other cloud platforms.

• Proficient in one or more programming languages such as

  Python, Java, C#, Node.js, etc.

• Strong hands-on experience in Python programming.
• Exposure to ML Ops practices and deployment workflows.
• Knowledge of cloud services and tools such as

  EC2, S3, Lambda, CloudFormation, Azure Functions, App Service, Storage, Google Compute Engine, Cloud Storage, Cloud Functions, etc.

• Knowledge of AI/ML services offered by GCP, Azure, and AWS.