Product Manager – AI & Automation

Central Region, Singapore
Permanent
Full-time

1 month ago

About ThunesThunes is the Smart Superhighway for money movement around the world. Thunes' proprietary Direct Global Network allows Members to make payments in real-time in over 130 countries and more than 80 currencies.Thunes' Network connects directly to over 7 billion mobile wallets and bank accounts worldwide, via more than 350 different payment methods, such as GCash, M-Pesa, Airtel, MTN, Orange, JazzCash, Easypaisa, AliPay, WeChat Pay and many more.Members of Thunes' Direct Global Network include gig economy giants like Uber and Deliveroo, super-apps like Grab and WeChat, MTOs, fintechs, PSPs and banks. Thunes' Direct Global Network differentiates itself through its worldwide reach, in-house Smart Treasury Management Platform and Fortress Compliance Infrastructure, ensuring Members of the Network receive unrivalled speed, control, visibility, protection and cost efficiencies when making real-time payments globally.Headquartered in Singapore, Thunes has offices in 12 locations, including Barcelona, Beijing, Dubai, London, Manila, Nairobi, Paris, Riyadh, San Francisco, Sao Paulo and Shanghai. For more information, visit:Context of the roleThunes is seeking a seasoned, technically fluent Product Manager - AI & Automation COE to spearhead our AI-driven transformation across the organization. Reporting to the Data Lead, you will define and execute a strategic roadmap that embeds AI and automation into the core of our global cross-border payments platform - driving both revenue growth and operational efficiency.We're looking for someone who has spent immersely in AI and data, with deep technical expertise, but who also brings a strong product and business mindset to the table.You've likely built, deployed, or scaled AI systems in production - whether as an engineer, researcher, or data lead - and now want to own the “what and why,” not just the “how.” You understand not just how AI works under the hood, but how to apply it meaningfully in a business context - prioritising what to build, what to automate, and what drives real impact.This role sits at the intersection of product strategy, data science, and engineering execution. You'll collaborate closely across all product squads , engineering, compliance, treasury, and operations to turn complex business needs into scalable, intelligent solutions. From identifying high-impact use cases to launching AI-first features, you'll lead initiatives from 0→1 and beyond.Success in this role requires hands-on experience delivering real-world AI products, a deep understanding of large-scale data ecosystems, and the ability to connect technical solutions to business outcomes. You should be comfortable designing for automation, scalability, and regulatory compliance - with a clear sense of how APIs and AI infrastructure can be leveraged to build future-ready financial products.Key ResponsibilitiesAI & Transformation Strategy

Define Thunes' AI adoption strategy & roadmap from the ground up - assessing departmental readiness across data maturity, cultural openness, and aligning each initiative with clear business priorities
Identify, prioritise, and categorise AI-first opportunities across departments (e.g., payments, compliance, treasury, customer support) - grouping them into revenue drivers (e.g., personalisation, smart FX routing) and efficiency enablers (e.g., intelligent automation, reconciliation operations)
Develop internal AI playbooks to identify and prioritise opportunities across products, operations, compliance, treasury, and support - including clear criteria for selecting the right approach, whether LLMs, predictive models, automation, or rules-based logic
Propose AI sequencing strategy - what to build, buy, or prototype in-house over 6-18 months
Lead experimentation with emerging agentic AI capabilities (e.g., autonomous agents, self-healing workflows), while developing ROI frameworks that weigh time-to-market, infrastructure cost, and operational impact
Evaluate and recommend vendors or open-source models that align with Thunes' regulatory and infrastructure context, while partnering with leadership to embed AI goals into company OKRs to drive measurable business impact
Work with Legal, Risk, and Compliance to ensure AI products meet regulatory and ethical guidelines

Hands on-Technical Product Management

Drive a "scalability-first" mindset within the product development process, ensuring that new features and enhancements are architected for future growth and increasing transaction volumes
Translate high-impact business problems into AI/ML product specifications, user stories, and roadmaps - collaborating with data scientists and PMs to design effective model workflows
Write detailed functional/tech specs for AI-powered features, collaborating with design and frontend/backend engineers
Partner with Data, Product & Engineering teams to build scalable intelligence layers - whether via foundational AI capabilities (e.g., LLM orchestration, RAG, inference layers), rules-based systems, ML, or automation - based on what best fits the use case. Focus on pragmatic, high-impact solutions that balance time-to-market, scalability, and agility
Work with engineering to determine and define infrastructure and deployment requirements for AI systems - whether on-premise, cloud-native, or hybrid - based on the specific use case, while accounting for regulatory requirements, data residency, and cost-efficiency. Ensure solutions are scalable, compliant, and sustainable

KPI Definition & Performance Measurement

Define and track key performance indicators (KPIs) related to platform performance, scalability, and operational efficiency to ensure sustainable growth
Define success metrics for each AI initiative - including model performance (e.g., accuracy, latency), user adoption, and business outcomes (e.g., NPS uplift, cost reduction, or revenue impact)
Establish baselines and compare outcomes through A/B testing or historical analysis to measure the lift from AI vs. traditional or rule-based approaches
Collaborate with analytics teams to build real-time dashboards and reporting tools that track product usage, model quality, and operational efficiency
Report impact regularly to leadership, tying AI initiatives to company-wide OKRs, operational KPIs, and ROI to inform future prioritisation and strategy

Cross-Functional Alignment & Execution

Partner with functional teams/leaders across compliance, treasury, operations, product, and marketing to surface high-impact, real-world AI use cases that align with business goals
Collaborate closely with legal and compliance to ensure all AI systems meet regulatory, ethical, and internal standards - especially critical in fintech and payments
Act as the bridge between technical and business teams, translating value, feasibility, and timelines clearly, while maintaining a centralised backlog of AI initiatives with cross-team dependencies
Drive education and transparency, helping teams understand the potential and limitations of AI, while ensuring features are well-integrated, non-duplicative, and tied to shared success metrics (e.g., NPS, revenue, cost-per-ticket)
Foster alignment rituals, including regular stakeholder reviews, product syncs, and impact reporting - promoting responsible AI development and cross-functional momentum

What we are looking forWe're looking for a hands-on AI and Automation expert - someone who's spent the bulk of their career building, deploying, or scaling AI product's, and now wants to bring that expertise into a strategic product role.At Thunes, we have deep payments expertise - but we're looking to complement that with true depth in AI. You don't need to come from a traditional product management background; what matters is that you've lived and breathed AI, understand its evolving landscape, and know how to bridge the gap between cutting-edge capability and real business value.

Have 5+ years of hands-on experience working in AI, machine learning, data science, automation or AI infrastructure - regulated environment preferred but not necessarily required
Have worked on real-world AI products or systems - from model development to deployment and monitoring - and understand the trade-offs across approaches (e.g., rules-based, ML, GenAI)
Strong academic background in a technical field such as AI & ML, Computer Science, Software Engineering, or a related discipline. Advanced Degree is highly preferred
Deep understanding of modern software architectures, distributed systems, and cloud technologies
Ability to evaluate when to use LLMs, RAG, automation, or traditional logic - and more importantly, when not to
Comfortable engaging with product, engineering, compliance, and business stakeholders to frame AI use cases in terms of outcomes, not just capabilities
Proven ability to engage in technical discussions with engineering teams and understand the implications of architectural decisions on scalability and performance
Demonstrated track record of successfully delivering products that have achieved significant scale and operational efficiency improvements
Exceptional analytical and problem-solving skills with a strong ability to identify bottlenecks, inefficiencies, and opportunities for process optimisation within complex systems
Detail-oriented with a passion for leveraging data and technology to drive improvements in operational performance and scalability
Proven ability to define and drive product initiatives focused on improving platform scalability, reliability, and operational efficiency
Excellent verbal and written English skills are critical to craft clear technical requirements, design documentation, and effectively communicate complex technical information to diverse stakeholders

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