Project/Delivery Manager

Rapsys Technologies Pte Ltd.; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Rapsys Technologies Pte Ltd. in Singapore is seeking an experienced Project/Delivery Manager to lead complex AI, data, and digital media delivery initiatives, coordinating cross-functional teams to ensure successful outcomes.

You will own project governance, risk management, stakeholder communications, and agile delivery ceremonies, guiding teams from concept through production with a focus on quality, timeliness, and alignment with business objectives.

Qualifications

• Minimum 9+ years of end-to-end technology or digital transformation project delivery.
• Hands-on AI, data, or automation project experience is highly desirable.
• Strong governance, data privacy, and security awareness.

Responsibilities

• Lead and coordinate cross-functional project teams across business, product, data, AI, and engineering.
• Define scope, milestones, data requirements, and success metrics for delivery.
• Ensure timely, high-quality production release and governance compliance.
• Provide regular dashboards and executive updates to stakeholders.
• Proactively manage RAID risks and dependencies throughout lifecycle.

Skills

Project management

Agile/Scrum

Stakeholder management

Team leadership

Jira

Education

Bachelor's degree in IT/CS/Engineering

PM certifications (PMP/PRINCE2/CSM/PSM/PMI-ACP)

Tools

Jira

Confluence

Microsoft Teams

Microsoft Office

Job description

We're Hiring: Project/Delivery Manager!

We are searching for an experienced and proactive Project/Delivery Manager to lead and deliver complex projects efficiently. The ideal candidate will have a strong background in project management, excellent leadership skills, and the ability to manage cross-functional teams to ensure successful delivery of business objectives.

Location: Singapore, Singapore
Work Mode: Work from Office
Role: Project/Delivery Manager

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 milestone 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 development or digital media delivery.

AI Delivery Management

• Work with business owners and technical teams to translate AI use cases into deliverable scope, with clear hypotheses, evaluation criteria, and go or no-go checkpoints between proof of concept, pilot, and production.
• Track data dependencies — data availability, quality, access approvals, and licensing — and escalates early where they place delivery or model performance at risk.
• Coordinate model evaluation and user acceptance activities with business and technical stakeholders, ensuring agreed accuracy, safety, and performance thresholds are met before production release.
• Ensure AI solutions are assessed for data privacy, security, intellectual property, bias, and human oversight requirements, and that the required approvals are documented before deployment.
• Manage expectations on AI outcomes, communicating clearly where results are exploratory, where confidence is limited, and where further data or iteration is required.

Stakeholder & Team Management

• Facilitate project governance meetings, sprint reviews, steering committee meetings, and regular project status updates.
• Prepare and present project dashboards, status reports, and executive updates to stakeholders.
• Manage stakeholder expectations, priorities, and project communications throughout the project lifecycle.
• Coordinate with other project managers and cross-functional teams to manage dependencies and promote delivery best practices.
• Work closely with external vendors, AI platform and model providers, and delivery partners to monitor progress, resolve issues, and ensure contractual deliverables are met.

Agile Delivery & Team Leadership

• Lead Agile delivery ceremonies including daily stand-ups, sprint planning, sprint reviews, retrospectives, and backlog refinement where applicable.
• Work closely with Product Owners to support backlog prioritization, release planning, and sprint execution.
• Track sprint progress, remove delivery impediments where appropriate, and work with delivery teams to ensure quality and timely completion of committed work.
• Coordinate BAU activities, production support, and minor enhancements — including post-deployment model monitoring, retraining, and prompt or configuration tuning — while ensuring minimal impact to project delivery and service availability.

Risk, Issue & Dependency Management

• Proactively identify, assess, and manage project risks, issues, assumptions, and dependencies (RAID), including risks specific to AI delivery such as data quality, model drift, hallucination, and over-reliance on automated outputs.
• Maintain RAID logs and ensure timely follow-up and resolution of action items.
• Escalate critical issues and project blockers promptly, providing mitigation and recovery plans where necessary.

Governance & Compliance

• Ensure project documentation, governance artefacts, and reporting comply with Mediacorp’s project management standards, AI governance requirements, and audit requirements.
• Follow Mediacorp’s security, data protection, responsible AI, compliance, change management, and organizational policies.
• Adhere to Mediacorp’s working hours, calendars, and project governance processes.

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, explainability, and intellectual property considerations.
• Strong practical experience with Agile and Scrum methodologies, including facilitating Agile ceremonies and managing iterative delivery.
• Demonstrated ability to manage multiple concurrent projects, competing priorities, and cross-functional teams in a fast-paced environment.
• Excellent stakeholder management, communication, presentation, and negotiation skills across both business and technical audiences, including the ability to explain AI concepts and limitations to non-technical stakeholders.
• Strong analytical and problem-solving skills with the ability to proactively identify risks and drive issue resolution.
• Experience managing external vendors, system integrators, and delivery partners is an advantage.
• Familiarity with BAU support processes, production support, and platform or service performance management is desirable.
• Proficient in modern project delivery and collaboration platforms, including Jira, Confluence, Microsoft Teams, and Microsoft Office.
• Hands-on use of AI-assisted productivity tools such as Microsoft Copilot, ChatGPT Enterprise, GitHub Copilot, or equivalent solutions to enhance planning, documentation, reporting, and team collaboration.
• PMP, PRINCE2 Practitioner, Certified ScrumMaster (CSM), Professional Scrum Master (PSM), PMI-ACP, or equivalent project management certifications are advantageous. AI or cloud certifications (for example Microsoft Azure AI, AWS Machine Learning, or Google Cloud AI) are a plus.