Head of AI Projects

About Us MetaComp is a Singapore-based digital payment and financial technology company operating within the regulated digital asset and payments ecosystem. As part of Alpha Ladder Group, we operate across payments, digital assets, capital markets, asset tokenization and financial technology infrastructure. We are building the next generation of regulated financial infrastructure, with a strong focus on technology, automation, data and artificial intelligence to improve operational efficiency, risk management and customer experience. About the Role We are looking for a Head of AI Projects to lead the identification, prioritization and delivery of AI-driven initiatives across the Group. This is a business-facing AI leadership role that combines AI strategy, project management, product thinking and cross-functional execution. You will work closely with senior management, Product, Engineering, Operations, Compliance, Risk and other business teams to identify high-value AI opportunities and turn them into scalable, production-ready solutions. The ideal candidate is someone who understands both what AI can do and how to make AI projects work in a real business environment — from defining the use case and business case, to coordinating technical development, managing stakeholders, measuring outcomes and driving adoption. Key Responsibilities 1. AI Strategy & Roadmap • Develop and execute the Group's AI project roadmap in alignment with business priorities. • Identify opportunities where AI, automation, machine learning and intelligent workflows can create measurable business value. • Work with senior management to evaluate and prioritize AI initiatives based on business impact, feasibility, risk and implementation complexity. • Establish frameworks for assessing AI use cases, project ROI and scalability. • Stay current with developments in generative AI, AI agents, LLMs, machine learning and emerging AI technologies. 2. AI Project Leadership • Own the end-to-end delivery of strategic AI projects from ideation through implementation and continuous improvement. • Define project scope, objectives, milestones, deliverables, resources and success metrics. • Translate business requirements into clear AI/product requirements for Engineering and technical teams. • Coordinate multiple workstreams and ensure projects are delivered on time and within agreed scope. • Identify and resolve project risks, dependencies and delivery issues. • Establish appropriate project governance, documentation and reporting mechanisms. 3. Cross-Functional Collaboration • Act as the key bridge between business stakeholders and AI/Engineering teams. • Work closely with Product, Engineering, Data, Operations, Compliance, Risk, Legal and other functions to ensure AI solutions address real business needs. • Facilitate workshops to identify opportunities for AI automation and process optimization. • Communicate complex AI concepts and technical considerations clearly to non-technical stakeholders. • Drive alignment among stakeholders and senior management throughout the project lifecycle. 4. AI Product & Solution Development • Lead the evaluation and implementation of AI solutions including LLM applications, AI agents, workflow automation, intelligent search, document intelligence and predictive analytics. • Partner with Product and Engineering teams to define MVPs, prototypes and production solutions. • Assess build-vs-buy opportunities and evaluate external AI vendors, platforms and technologies. • Establish appropriate testing, evaluation and performance measurement frameworks for AI solutions. • Drive continuous improvement based on user feedback, performance data and business outcomes. 5. AI Governance, Risk & Compliance • Work with Compliance, Risk, Legal and Technology teams to ensure AI initiatives are developed and deployed responsibly. • Establish appropriate governance principles covering AI security, data privacy, model risk, access controls and human oversight. • Ensure AI projects operating within regulated financial services environments meet applicable internal policies and regulatory expectations. • Identify potential operational, technology and regulatory risks associated with AI adoption and establish appropriate controls. 6. Business Transformation & Adoption • Identify opportunities to use AI to improve productivity, reduce manual processes and enhance decision-making. • Drive adoption of AI solutions across business functions rather than focusing solely on technical deployment. • Define KPIs and measure the business impact of AI initiatives, including productivity gains, cost savings, turnaround time and quality improvements. • Develop change-management and training approaches to support successful adoption. • Promote responsible and practical adoption of AI across the organization. 7. Team & Capability Building • Build and lead an AI project management / AI transformation capability as the function grows. • Mentor project managers, product managers and other team members involved in AI initiatives. • Establish best practices, methodologies and reusable frameworks for AI project delivery. • Develop relationships with external AI technology providers, consultants and strategic partners where appropriate. Key AI Project Areas Depending on business priorities, projects may include: • AI-powered internal productivity and workflow automation • AI agents and intelligent business workflows • AI-assisted compliance and regulatory operations • KYC / AML and transaction monitoring enhancements • Intelligent document processing and information extraction • AI-powered customer and employee support • AI-assisted research and knowledge management • Risk analytics and anomaly detection • AI-enabled financial and operational analytics • Internal AI knowledge platforms and enterprise search • AI integration with existing products and business systems • Generative AI appli…