AI Cloud Architect

3 weeks ago

Noida, India HCLTech Full time

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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