This role is critical for driving the successful delivery of Cloud, Data Engineering, and AI/ML initiatives. The individual will serve as a technical and project leader, ensuring end-to-end execution from planning to deployment while maintaining alignment with business objectives, stakeholder expectations, and technical excellence. The position demands a strategic mindset with the ability to manage cross-functional teams, govern project delivery, and implement scalable, secure, and cost-efficient cloud solutions across AWS, Azure, or GCP platforms. Responsibilities: • Lead end-to-end delivery of Cloud, Data Engineering, and AI/ML projects from inception to production. • Design and oversee cloud architectures on AWS, Azure, or GCP, ensuring security, scalability, and cost optimization. • Develop and manage data pipelines and AI/ML workflows, including model training, validation, deployment, and MLOps integration. • Coordinate and mentor cross-functional teams including Data Engineers, ML Engineers, and Cloud Developers. • Manage stakeholder relationships through effective requirement gathering, progress reporting, and escalation resolution. • Apply Agile methodologies to drive iterative delivery, maintain delivery governance, and proactively manage risks and project timelines. Requirements Requirements: • Proven experience managing end-to-end delivery of Cloud, Data Engineering, and AI/ML projects. • In-depth hands-on knowledge of AWS, Azure, or GCP architecture, deployments, security, and cost optimization. • Solid understanding of AI/ML workflows and MLOps practices, including model lifecycle management. • Demonstrated leadership in guiding cross-functional technical teams and ensuring delivery alignment. • Strong client and stakeholder management skills with experience in requirement gathering and progress communication. • Expertise in Agile delivery, project planning, risk management, and delivery governance.