Drive successful delivery of Cloud, Data Engineering, and AI/ML initiatives as a Technical Delivery Manager.

About the Company

Kumaran Systems specializes in engineering future-ready transformations since 1992, helping enterprises bridge the past and the future by reimagining legacy systems and embracing AI-led possibilities. With over 34 years of delivery excellence, they focus on re-engineering core applications, driving cloud transformation, and creating automation-first, GenAI-enabled ecosystems in industries like Banking, Financial Services, Insurance, Telecom, and Automotive. Their approach blends engineering discipline with AI innovation, ensuring agility and responsiveness for clients.

Role Overview

As a Technical Delivery Manager, you will play a critical role in driving the successful delivery of Cloud, Data Engineering, and AI/ML initiatives. This position requires both technical and project leadership, allowing for end-to-end execution from planning to deployment while ensuring alignment with business objectives, stakeholder expectations, and technical excellence. The ideal candidate will possess a strategic mindset and the ability to manage cross-functional teams effectively.

Key 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.

Tech Stack

• Cloud Platforms: AWS, Azure, GCP
• Technologies: AI/ML, Data Engineering, MLOps
• Methodologies: Agile
• Tools: Project management and collaboration software (not explicitly mentioned)

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.

Benefits

• Competitive salary package.
• Opportunity to work on cutting-edge technologies in a collaborative environment.
• Continuous learning and professional development opportunities.
• Flexible working hours and a supportive team culture.
• Health and wellness programs.