Cloud Innovator

22 hours ago

Vellore, Tamil Nadu, India beBeeCloud Full time ₹ 1,80,00,000 - ₹ 2,40,00,000
Unlock Business Transformation with AI Solutions

Transform business outcomes through cutting-edge cloud-based AI innovations.

As a Cloud AI Architect, you will be responsible for designing and implementing AI-powered cloud infrastructures that drive business value and scalability.

  • Designing AI-Powered Cloud Infrastructures: Select and implement appropriate cloud services to ensure seamless integration of AI models into existing cloud infrastructure and applications.

Key Responsibilities:

  • Develop and maintain scalable and secure cloud architectures to support AI workloads.
  • Integrate AI models with cloud-native MLOps pipelines for continuous training, deployment, and monitoring.
  • Collaborate with cross-functional teams to design and implement responsible AI frameworks ensuring bias mitigation and fairness.
  • Implement multi-cloud AI strategies and hybrid-cloud integration for flexibility and disaster recovery.
  • Drive cost optimization of AI workloads via cloud resource tuning and autoscaling.

Requirements:

  • 10-15 years of experience in cloud architecture with 5+ years specializing in AI/ML system design and deployment.
  • Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or related field.
  • Deep knowledge of AI/ML frameworks integrated with cloud platforms.
  • Proficient with cloud AI services: Azure AI, AWS AI/ML, Google AI Platform.
  • Experience with MLOps tools: Kubeflow, MLflow, Azure MLOps.
  • Strong programming skills in Python, R, or Java.
  • Understanding of data engineering concepts and cloud data platforms.
  • Familiarity with cloud security standards and data privacy regulations.
  • Excellent leadership and stakeholder management skills.

Desired Competencies:

  • Advanced AI/ML certifications.
  • Experience with cutting-edge AI technologies like NLP, computer vision, reinforcement learning.
  • Knowledge of emerging AI regulations and ethical AI standards.
  • Experience with container orchestration (Kubernetes) for scalable AI deployments.

Additional Considerations:

  • Designing and implementing responsible AI and ethical AI frameworks ensuring bias mitigation and fairness.
  • Collaborating on AI governance and compliance with evolving data privacy laws.

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