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AI Cloud Architect

AI Cloud Architect

HCLTechnellore, India
15 hours ago
Job description

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.
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