Project/Delivery Manager-digital transformations,AI, machine learning, generative AI, data platform

Key Responsibilities Project Planning & Execution · Collaborate with business, product, data, AI and engineering, architecture, and QA teams to define project scope, objectives, deliverables, dependencies, data requirements, and success criteria, including model performance, quality, and adoption measures.

· Develop and maintain comprehensive project plans, schedules, resource allocation, and mile stone tracking. · Manage the full project lifecycle from initiation and proof of concept through pilot, production deployment, transition to operations, and project closure.

· Monitor project progress against scope, schedule, and key deliverables — including data readiness, model development and evaluation, integration, and testing milestones — ensuring timely and high-quality delivery.

· Coordinate project change requests and assess their impact on project scope, timeline, cost, and resources, allowing for the iterative and experimental nature of AI develop mentor digital media delivery.

Qualifications

& Experience · Bachelor’s degree in Information Technology, Computer Science, Engineering, Business, or a related discipline.

· Minimum 9+ years of proven experience managing end-to-end technology or digital transformation projects, including hands-on delivery of AI, data, digital media or intelligent automation initiatives.

· Experience delivering AI, machine learning, generative AI, data platform, or automation projects from proof of concept through to production is highly desirable.

· Working knowledge of AI delivery concepts — data pipelines and data readiness, model training and evaluation, generative AI and large language models, retrieval-augmented generation, prompt engineering, and MLOps — sufficient to plan work, challenge estimates, and manage technical trade-offs.

· Understanding of AI governance and responsible AI practices, including data privacy and PDPA obligations, model risk, bias, explain ability, and intellectual property considerations. · Strong practic