AI Project Management Operations

Confidential; Kuala Lumpur; On-site; MYR 180,000 - 300,000; Full time

Job summary

Confidential in Kuala Lumpur seeks a Project Management Operations Manager / Assistant Manager (MTO) to own marketing's AI and automation agenda end to end, shaping initiatives from discovery to delivery and adoption tracking. You will run 3-5 concurrent streams, align stakeholders, and measure ROI.

Responsibilities include PMO delivery, data governance, vendor/build decisions, and ensuring tool adoption across marketing. Fluent English and Mandarin required.

Qualifications

• 5+ years in project/program management or product management, with AI/ML-driven initiatives experience
• Strong stakeholder negotiation and governance skills
• Familiarity with MLOps fundamentals and cloud AI services
• Experience with no-code/low-code validation and prototyping

Responsibilities

• Own the roadmap and prioritization of AI/automation initiatives across marketing, aligning technical feasibility with business impact.
• Translate ambiguous problems into scoped, sequenced initiatives with clear success metrics.
• Run market/tool discovery to identify high-value AI use cases and validate through rapid prototyping.
• Own evaluation, vendor/build decisions for AI platforms, including build-vs-buy trade-offs.
• Establish adoption tracking and ROI measurement for deployed AI tools.
• Champion AI adoption through executive briefings and change management.

Job description

The Project Management Operations Manager / Assistant Manager (MTO) owns marketing's AI and automation agenda end to end, from identifying high-value opportunities through vendor or build evaluation to delivery and adoption tracking. This role serves as the PMO function that turns AI opportunity into shipped, measured outcomes, scoping initiatives, sequencing delivery across 3-5 concurrent workstreams, and ensuring successful adoption. The role shapes AI product direction by turning ambiguous business challenges into prioritized, high-value solutions, and provides the PMO discipline to keep timelines, resources, and risk under control across concurrent initiatives. It also closes the gap between technical capability and business value, through stakeholder alignment, ROI tracking, and structured adoption frameworks.

Job Responsibilities:

• Own the roadmap and prioritization of marketing's AI/automation initiatives (e.g. AI-assisted content, personalization, trading/marketing copilots, workflow automation), balancing technical feasibility against business impact.
• Translate ambiguous business problems into scoped, sequenced initiatives with clear success metrics before build begins.
• Run market/tool discovery to identify high-value AI and automation use cases across marketing functions; validate through rapid prototyping before committing engineering resource.
• Own the evaluation and vendor/build decision process for AI-native and AI-augmented platforms, including build-vs-buy trade-offs.
• Establish adoption tracking and ROI measurement mechanisms for every deployed AI/automation tool (e.g. time saved, cost avoided, efficiency gains).
• Champion AI/automation adoption internally through executive briefings, user training, and change management initiatives to drive tool utilization.

AI & Automation Delivery (Technical Enablement)

• Assess AI-readiness across the marketing stack, identifying data quality issues and integration gaps with Data and IT.
• Define and enforce data governance standards for marketing data used in AI workflows.
• Support technical implementation of AI-powered lifecycle, personalization, and agent-based use cases alongside engineering/Data teams.
• Curate reusable assets (evaluation checklists, prompt/workflow templates, rollout playbooks) to speed up future AI/automation deployments.
• Partner with AI and IT teams to ensure AI solutions meet scalability and regulatory requirements.

Project & Program Management (PMO)

• Manage end-to-end delivery of cross-functional marketing projects, coordinate cross-functional teams and external vendors.
• Own project planning, timelines, dependencies, risk logs, and stakeholder communication across concurrent initiatives.
• Implement standardized delivery frameworks (agile/hybrid) with stage gates for higher-risk or higher-spend initiatives.
• Track portfolio health: on-time delivery rate, resource utilization, and blocked/at-risk initiatives, and elevate early.
• Build and maintain reporting frameworks for project delivery health, AI/automation adoption, and operational KPIs.
• Identify bottlenecks and process gaps across marketing operations, and drive improvement through process redesign, automation, and tooling.

Job Requirements:

Core Skills

• Proven hands-on experience with LLM application development, including prompt engineering, RAG (Retrieval-Augmented Generation), and AI agent frameworks (e.g. LangChain, AutoGen, LlamaIndex), with the judgment to scope, evaluate, and guide build/vendor decisions.
• Experience integrating with APIs.
• Experience evaluating or deploying AI agents, copilots, or automation tools within a business function, beyond IT-led rollouts.
• Ability to prototype without coding, using no-code/low-code tools to validate concepts before committing engineering resource.
• Strong stakeholder negotiation skills, with proven ability to align engineering, business leads, and senior leadership on priorities amid ambiguity.
• Experience in consulting or fintech environments, comfortable scoping solutions under tight deadlines and ambiguous requirements.
• Understanding of AI-readiness fundamentals, including data quality, integration gaps, and governance considerations, necessary to assess AI use case viability.
• Comfortable running a portfolio of concurrent projects with formal tracking (Jira, Asana, or equivalent) and reporting up on status, risk, and budget.
• Analytical mindset; comfortable with dashboards and data pipelines - SQL or equivalent is a plus.
• Experience working in fast-paced, matrixed organizations.

Nice to Have

• Familiarity with agile / hybrid project delivery methods.
• Experience in regulated industries (e.g. financial services, brokerage, fintech).

Qualifications

• 5+ years in project/program management or product management, with at least 2 years focused specifically on AI/ML-driven products or initiatives (GenAI, automation, predictive or personalization systems).
• Proven track record owning product-level metrics (adoption rate, feature usage, ROI) across a portfolio of concurrent initiatives, not just delivery status.
• Working familiarity with MLOps fundamentals (data versioning, model/drift monitoring) and cloud AI services (e.g. AWS Bedrock, AWS SageMaker, Azure ML), sufficient to hold informed conversations with engineering.
• Strong PMO fundamentals: resource forecasting, risk mitigation, and post-mortem analysis on complex, technically ambiguous initiatives.
• Fluent in English and Mandarin, to liaise with internal and external stakeholders based overseas.