Senior Executive, AI Cloud Engineer

Job Description: Key Responsibilities • Cloud Architecture Design: Develop and maintain scalable, secure cloud solutions that support complex deployments, including those using AI and machine learning models. Design architectures that optimize for cost, performance, and security. • Service Management: Implement, monitor, and manage cloud services across multiple platforms (AWS, Azure, Google Cloud), including compute, networking, storage, and more. Ensure optimal allocation and utilization of cloud resources. • Automation: Automate cloud deployments and configuration management using tools like Terraform, Ansible, and Kubernetes to enhance operational efficiencies and reduce the potential for human error. • Security and Compliance: Apply and maintain security standards across the cloud infrastructure, including managing firewalls, VPNs, and access controls. Ensure compliance with industry regulations and data protection standards. • Performance Monitoring: Monitor cloud infrastructure performance, implement strategies for logging, monitoring, and alerting to detect and resolve issues promptly. • Disaster Recovery and Backup: Design and implement disaster recovery plans to ensure continuous availability and rapid recovery of applications in case of failure. • Cost Optimization: Monitor and optimize spending to ensure efficient use of cloud resources. Use tools and strategies to reduce costs without compromising on performance or security. • Collaboration and Support: Work closely with IT teams, developers, and business units to provide cloud solutions and support. Educate team members on cloud technologies and best practices. Requirements & Skills (Not all mandatory, but should have touched maximum ) 1. Core Technical Skills: • Programming Languages: Proficiency in scripting and programming languages such as Python, Ruby, Java, or Bash is crucial for automation and developing cloud applications. • Infrastructure as Code (IaC): Expertise in using IaC tools like Terraform, Ansible, and AWS CloudFormation to automate the setup and management of cloud environments. • Containerization and Orchestration: Skills in Docker for containerization and Kubernetes or Docker Swarm for orchestration to manage containerized applications efficiently. • Networking: Deep understanding of network technologies including DNS, TCP/IP, SSL, DHCP, Load Balancing, and VPNs. 2. Cloud Platform Expertise: • Amazon Web Services (AWS): Skills in managing and deploying on AWS services such as EC2, S3, RDS, ELB, ECS, EKS, Lambda, and VPC. • Microsoft Azure: Experience with Azure services including VMs, App Services, Azure SQL Database, Azure Kubernetes Service, and Azure Functions. • Google Cloud Platform (GCP): Knowledge of GCP services like Compute Engine, App Engine, Kubernetes Engine, Cloud Functions, and BigQuery. 3. Security Skills: • Cloud Security: Knowledge of security best practices and industry security standards such as ISO 27001, SOC 2, or PCI DSS. • Identity and Access Management (IAM): Experience with IAM policies and tools to manage access to cloud resources securely. • Data Encryption and Security Protocols: Understanding of encryption techniques and protocols to secure data in transit and at rest. 4. Certifications: • Vendor-Specific Certifications: • AWS Certified Solutions Architect – Professional • AWS Certified DevOps Engineer – Professional • Microsoft Certified: Azure DevOps Engineer Expert • Google Professional Cloud Architect • Google Professional Cloud DevOps Engineer • General Cloud Certifications: • Certified Cloud Security Professional (CCSP) • CompTIA Cloud+ • Networking and Security Certifications: • Cisco Certified Network Associate or Professional (CCNA/CCNP) • Certified Information Systems Security Professional (CISSP) 5. DevOps Practices: • Continuous Integration/Continuous Deployment (CI/CD): Skills in setting up and maintaining CI/CD pipelines using tools like Jenkins, GitLab CI, or CircleCI. • Monitoring and Logging: Proficiency with tools like Prometheus, Grafana, ELK Stack (Elasticsearch, Logstash, Kibana), or similar technologies to monitor cloud resources and applications. 6. Performance Optimization: • Resource Management: Skills in cost optimization, performance tuning, and ensuring high availability and fault tolerance in cloud deployments. • Scalability: Experience in designing systems that efficiently scale horizontally and vertically based on application load. Educational Qualifications • Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field. • Professional certifications related to cloud architecture, such as AWS Certified Solutions Architect, Microsoft Certified: Azure Solutions Architect Expert, or Google Professional Cloud Architect.