New opportunity

VP - Technical Product Owner (AI & Automation)

Singapore Exchange · Singapore

About this role

The Singapore Exchange (SGX) is seeking a VP - Technical Product Owner (AI & Automation) to drive initiatives from problem definition to production outcomes. This role involves partnering with business owners to translate user problems into measurable product outcomes, shaping scope, and providing clarity to engineering teams. You will not write production code but must be technically fluent enough to challenge engineering decisions, prototype with AI agents, and earn the trust of senior engineering teams. Key responsibilities include: Product Analysis and Shaping: Develop deep product understanding, define north-star metrics and KPIs, and produce requirements, user stories, and AI-assisted product specifications. Roadmap and Prioritisation: Co-own the product roadmap, prioritize features based on evidence and technical feasibility, and manage vendor roadmaps. Stakeholder Management: Communicate product direction and progress, build consensus, and manage trade-offs in complex settings. Ways of Working: Utilize AI agents to accelerate discovery and prototyping, drive continuous discovery through interviews and data analysis, and contribute to SDLC improvements. Leadership: Lead and manage a team of Technical Product Owners and UX Designers, fostering a culture of innovation and ensuring system resiliency. Required Qualifications: Minimum 5 years of experience in product management, product ownership, business analysis, or engineering. Technical fluency in reading code, APIs, and data flows. Hands-on experience using AI agents for prototyping and validation. Strong product instinct, communication skills, and a builder mindset. Preferred Qualifications: Proven track record of leading large, complex products and teams. Domain expertise in capital markets infrastructure (exchanges, clearing houses, derivatives, trading platforms) or broader financial services.

For full details about this role, click “Apply on company site” to view the employer’s original posting.

Skills for this role

Product ManagementProduct OwnershipBusiness AnalysisAI AgentsPrototypingTechnical ArchitectureData FlowsAPI ReasoningStakeholder ManagementSDLCCapital MarketsFinancial Services

Checking your profile…

Preparation suggestions, not the employer’s actual interview questions. Always check the original posting for current requirements.

Understand the role

What matters most

Technical Credibility with Engineering
The role requires the ability to challenge engineering decisions and participate in architecture discussions without writing production code. You must demonstrate technical fluency in reading code, understanding API structures, and mapping data flows to earn the trust of senior engineering teams.
AI-Driven Product Discovery and Prototyping
You are expected to move beyond basic AI usage by employing AI agents to accelerate discovery, generate functional mockups, and validate product assumptions before committing engineering resources. This requires a hands-on approach to using AI for technical specification and rapid validation.
Evidence-Based Roadmap Management
You must co-own the product roadmap by prioritizing features based on measurable business outcomes, regulatory requirements, and technical feasibility. This involves defining north-star metrics and ensuring they are observable through data analysis and stakeholder consensus.
Leadership in Regulated Environments
As a VP, you must lead a team of TPOs and UX designers while maintaining a focus on system resiliency and stability, which are critical for capital markets infrastructure. You must balance the drive for innovation with the strict operational requirements of a regulated exchange.

Likely challenges to think through

Balancing Innovation with System Resiliency
SGX operates critical market infrastructure where stability is paramount. The challenge is introducing AI-driven automation and new SDLC practices without compromising the reliability of existing systems. Prepare by discussing how you manage risk in high-stakes environments and how you ensure new features meet rigorous stability standards.
Navigating Complex Stakeholder Landscapes
You will need to manage expectations across business owners, engineering teams, and external vendors while dealing with inherent product uncertainty. Prepare by detailing your framework for building consensus, making trade-offs explicit, and communicating technical progress to non-technical stakeholders.
Driving Decisions in Ambiguous Contexts
The role requires driving decisions rather than escalating them, even when requirements or technical paths are unclear. Prepare by sharing examples of how you have used data and prototyping to resolve ambiguity and move a product from problem definition to production outcome.

Practice your answers

Technical practice

Evaluating Technical Trade-offs in Financial Systems

What to coverDescribe your process for evaluating build-versus-buy decisions in a highly regulated environment like capital markets. Discuss how you balance the need for rapid innovation with the non-negotiable requirements for system resiliency and stability.

AI-Driven Prototyping and Validation

What to coverProvide an example of how you have used AI agents to accelerate the discovery or prototyping phase of a product. Explain how you validated the output of these agents to ensure the resulting specifications were technically sound before handing them off to engineering.

API Reasoning and Data Flow Analysis

What to coverHow do you approach reviewing complex data flows or API documentation to identify potential bottlenecks or integration risks? Explain how you use this technical understanding to provide clarity to engineering teams during the requirements phase.

Defining North-Star Metrics for AI Products

What to coverWhen implementing AI or automation features, how do you define measurable outcomes that align with business goals? Discuss how you partner with data teams to ensure these metrics are observable and actionable.

Managing Vendor Roadmaps

What to coverDescribe your strategy for aligning third-party software vendor roadmaps with internal company objectives. How do you manage the tension between vendor-driven updates and the specific needs of a capital markets infrastructure?

SDLC Evolution and AI Integration

What to coverAs AI changes how software is delivered, what specific improvements would you propose for the SDLC? Address how you would maintain high standards for system resiliency while adopting more agile, AI-native development practices.

Technical Fluency in Architecture Discussions

What to coverHow do you prepare to challenge engineering decisions without writing production code yourself? Explain how you build the necessary technical credibility to earn the trust of senior engineers during architectural reviews.

Prioritization in Regulated Environments

What to coverHow do you prioritize features when faced with conflicting demands from regulatory requirements, member needs, and technical debt? Explain how you use evidence-based approaches to drive consensus among stakeholders.

Behavioural practice

Driving Decisions Under Ambiguity

What to coverDescribe a situation where you had to make a critical product decision with incomplete information or conflicting stakeholder input. Explain the steps you took to frame the problem, gather evidence, and ultimately drive the team toward a decision.

Managing Complex Stakeholder Relationships

What to coverTell us about a time you had to communicate a difficult trade-off (e.g., scope reduction or timeline delay) to senior stakeholders. How did you build consensus and manage their expectations while maintaining the project's integrity?

Leading and Developing Product Teams

What to coverProvide an example of how you have mentored or led a team of product owners and UX designers. How do you foster a culture of innovation while ensuring the team remains focused on the stability and resiliency of the platform?

Adapting to Maturing Product Practices

What to coverDescribe a time you joined an organization where product or SDLC practices were still maturing. What specific actions did you take to contribute to these processes while simultaneously delivering on product outcomes?

Sharpen your knowledge

Topics to prepare

Capital Markets Infrastructure
Review the core components of exchange operations, including clearing, settlement, and derivatives trading. Exercise: Map out the data flow of a typical trade lifecycle from execution to clearing to identify potential automation bottlenecks. This is relevant as the role requires domain expertise in financial infrastructure to drive product strategy.
SDLC Evolution with AI
Study modern software development lifecycle practices that integrate AI-assisted workflows. Exercise: Draft a proposal on how AI agents can be integrated into existing SDLC phases to accelerate discovery and prototyping without compromising system resiliency. This is relevant because the role involves shaping how SGX evolves its development practices.

Skills to revise

AI Agent Prototyping
Gain hands-on experience using AI agents (e.g., AutoGPT, LangChain, or agentic coding assistants) to build functional prototypes or validate product assumptions. Exercise: Create a prototype for a hypothetical automated reporting tool using AI agents to generate requirements and mockups. This is a core requirement for validating product ideas before engineering investment.
Technical API and Data Flow Reasoning
Practice reading and interpreting API documentation and system architecture diagrams to understand data dependencies. Exercise: Take a complex system diagram and explain the potential failure points and trade-offs in the data flow to a non-technical stakeholder. This is essential for challenging engineering decisions and maintaining system stability.
Evidence-Based Prioritization
Develop frameworks for prioritizing features based on quantitative metrics and technical feasibility. Exercise: Build a prioritization matrix that balances regulatory requirements, business value, and technical debt for a simulated product roadmap. This is critical for the role's responsibility of co-owning the roadmap and managing trade-offs.

Your preparation checklist

Prepare an AI-driven prototyping case study
Develop a portfolio piece demonstrating how you used AI agents to accelerate product discovery or validation. Focus on a specific instance where you generated mockups, drafted technical specifications, or validated assumptions before engineering involvement.
Map your technical fluency to capital markets
Prepare to discuss your ability to read code, reason about API structures, and analyze data flows within a financial context. Be ready to explain how you have evaluated technical trade-offs in complex, regulated environments.
Formulate a framework for SDLC and AI integration
Draft a perspective on how AI tools can evolve the Software Development Life Cycle (SDLC). Be prepared to discuss how you would balance innovation with the high resiliency and stability requirements of critical financial infrastructure.
Develop a strategy for evidence-based prioritization
Create a structured approach for managing product roadmaps under ambiguity. Prepare examples of how you have used north-star metrics and KPIs to drive consensus among diverse stakeholders and manage build-versus-buy trade-offs.
Prepare questions on SGX's technical landscape
Draft thoughtful questions regarding the current maturity of SGX's AI-driven product practices, the specific challenges of integrating AI into their existing capital markets architecture, and how they define success for TPOs in their current regulatory environment.

Availability last checked: 18 Oct 2026. Status can change after a check; confirm on the employer’s website. Report an issue · Our checking policy

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