About this role
This role addresses the need to move financial services clients beyond simple, point-in-time analytics toward sophisticated, closed-loop decision systems. The core problem solved is the reliance on inconsistent human judgment or disconnected AI engines when making consequential decisions in areas like credit approval or fraud detection. The AI Specialist will be instrumental in engineering intelligent decision automation solutions that integrate predictive models, explicit business rules, and continuous feedback loops to create systems that are fast, consistent, and auditable.
The specialist will focus on embedding these solutions directly with clients across Asia, helping them define the strategy for automation, augmentation, and human oversight. This involves a deep technical breadth, spanning classical AI techniques like expert systems to modern machine learning and large language model integration. The goal is to build enduring capabilities rather than temporary projects.
This position is ideal for a seasoned practitioner who has a proven track record of building, deploying, and improving intelligent decision systems within demanding financial services environments. Success in this role requires a blend of deep theoretical knowledge and practical experience in production deployment.
What you will do
- Lead the design of end-to-end Enterprise Decision Management architectures, connecting data ingestion, predictive model scoring, business rule execution, and outcome measurement into production-grade services.
- Advise clients on decision strategy, determining which decisions should be automated, augmented, or retained by human judgment, and establishing governance frameworks.
- Decompose complex financial services decision domains, such as underwriting and fraud detection, into structured decision architectures using DMN and relevant standards.
- Design and oversee the development of predictive models, including scorecards and neural network approaches, that inform operational decision flows.
- Apply prescriptive analytics and mathematical optimization techniques to maximize decision outcomes at portfolio levels.
- Distinguish between rule engine integration concerns and rule service design, ensuring clear interfaces between model outputs and rule engine inputs.
- Integrate decision management capabilities with LLM and generative AI architectures, focusing on implementing rules-based guardrails over LLM outputs.
What you need
- Candidates must possess genuine depth across the full AI and decision management spectrum, including classical techniques like expert systems and case-based reasoning.
- Demonstrated experience is required in building, deploying, and improving intelligent decision systems within production financial services environments.
- Proficiency in designing and implementing decision architectures that connect data, scoring, rules, and measurement into coherent services is essential.
- Experience in applying predictive analytics, including methods like gradient boosting and neural networks, to operational decision flows is necessary.
- A strong understanding of prescriptive analytics and optimization techniques (e.g., linear programming) to maximize outcomes is required.
- Expertise in both rule engine integration architecture and the design/governance of business logic is a non-negotiable requirement.
- Familiarity with integrating modern AI components, specifically LLMs, with decision management systems is a key skill.
Nice to have
- Experience with MAS and HKMA regulatory requirements
- Experience with model risk management governance
Benefits
- Innovation Labs
- Be Yourself at Work culture
- Diverse, talented team across more than 30 offices worldwide
Skills and tech stack
Questions candidates ask
What is the remote policy for this role?
The posting describes this as a forward-deployed role where the specialist will be embedded with clients, building working solutions alongside their teams.
What is the expected compensation structure?
The posting does not specify salary details for this position.
What specific AI technologies are central to this role?
The role requires expertise across classical techniques such as expert systems and case-based reasoning, alongside modern machine learning and large language model integration.
What is the team structure like?
The specialist will play a defining role in building Capco's Enterprise Decision Management practice across Asia.