We are seeking a Senior Vice President, Applied AI Product Manager – Tech to translate high-value business and client opportunities into viable AI-enabled products, agents and workflow capabilities.
Working alongside the Applied AI Product Manager, you will convert the product vision and intended business outcomes into a clear technical product approach, MVP, delivery backlog and implementation pathway. You will work closely with designers, engineers, AI and data specialists, business teams and control functions to move selected opportunities from discovery through prototype, pilot and production handoff.
You will determine how AI should be applied, how human and AI activities should interact and what data, integrations, controls and evaluation methods are required. You will ensure that proposed products are usable, technically feasible, measurable, governable and appropriate for a highly regulated environment.
You will be expected to operate confidently in technical detail, make informed product trade-offs and provide clear direction to multidisciplinary delivery teams.
In this role, you will make an impact in the following ways:
Technical product definition
- Partner with the Applied AI Product Manager and Designer to translate business problems, client needs and product concepts into technically viable AI-enabled products and workflows.
- Define technical product vision, MVP scope, functional requirements, user stories, acceptance criteria and delivery roadmap.
- Own and prioritize the technical product backlog, balancing user value, business outcomes, feasibility, risk and delivery effort.
- Identify appropriate applications of generative AI, agentic workflows, intelligent automation and decision-support capabilities.
- Determine which activities should be automated, augmented, escalated or remain human-led.
AI product development and prototyping
- Shape AI-enabled workflows, agents, prototypes and proofs of concept in partnership with AI, data, engineering and design teams.
- Define requirements relating to data, integrations, permissions, model behavior, orchestration, user interaction and performance.
- Guide product decisions involving large language models, retrieval-augmented generation, knowledge systems, prompt and context design and agentic workflows.
- Use approved AI-enabled development and prototyping tools to accelerate research, requirements definition, experimentation and product delivery.
- Design experiments that test the most important product and technical assumptions before significant investment is committed.
Delivery, governance and measurable outcomes
- Lead the technical product journey from opportunity definition through prototype, MVP, pilot and production transition or handoff.
- Coordinate engineers, AI and data specialists, designers, platform teams and control partners to maintain delivery momentum and resolve dependencies.
- Establish evaluation criteria for product quality, reliability, model performance, user experience and business impact.
- Incorporate responsible AI, data, privacy, security, compliance and operational-resilience requirements from the outset.
- Use testing, user feedback and performance evidence to refine priorities and inform scale, redesign or stop decisions.
- Maintain alignment between the product vision, technical execution, user needs and expected value.
Stakeholder leadership and capability building
- Communicate technical product concepts, trade-offs and risks clearly to senior business, client and technology stakeholders.
- Build trusted relationships across product, design, engineering, AI, data, operations, risk and business teams.
- Create alignment between business and technical stakeholders and ensure key decisions are made at the appropriate level.
- Provide direction and accountability across small, multidisciplinary delivery teams.
- Mentor colleagues and strengthen applied AI and technical product-management capabilities across APAC.
- Contribute reusable methods, patterns and practices that improve the quality and speed of future AI product delivery.
What we are looking for
The ideal candidate combines senior product-management experience, practical AI fluency, financial services knowledge and the ability to translate strategic intent into executable technical products.
You will bring:
- Significant experience, typically 15 years or more across technical product management, technology-led transformation, innovation, consulting or enterprise delivery.
- Recent experience shaping, building or scaling AI-enabled products, platforms, agents, workflow capabilities or intelligent automation.
- Strong financial services expertise, ideally across banking, asset servicing, capital markets, payments, operations, risk, compliance or enterprise data.
- Demonstrated ability to translate ambiguous business challenges into MVPs, product backlogs, requirements, roadmaps, prototypes and delivery plans.
- Strong understanding of generative AI, large language model applications, intelligent automation, agentic workflows and responsible AI principles.
- Practical familiarity with AI methods such as prompt and context design, retrieval-augmented generation, knowledge graphs, model evaluation or agent orchestration.
- Working knowledge of enterprise technology concepts, including APIs, data flows, integration patterns, permissions, security and production readiness.
- Experience taking enterprise products from discovery and prototype through pilot, adoption and production transition.
- Experience using AI-assisted development, coding or prototyping tools would be advantageous.
- Experience operating within complex, regulated and highly governed environments.
- Strong executive communication, stakeholder management, prioritization and delivery-leadership skills.
- A record of delivering measurable business or client outcomes rather than outputs alone.
- Relevant product, agile, AI or industry qualifications would be beneficial; equivalent practical experience will also be considered.
Behavioral attributes
The strongest candidates will be:
- Technically curious and able to evaluate emerging AI capabilities critically.
- Comfortable moving between product strategy, technical requirements and delivery detail.
- Commercially aware and focused on applying technology to meaningful business and client problems.
- Collaborative and low ego, with the ability to work across business, design and technical disciplines.
- Able to create clarity and momentum when the product or delivery path is still evolving.
- Open to challenge and willing to change direction when evidence invalidates an assumption.
- Resilient in a fast-moving environment with changing priorities.
- Risk-aware and thoughtful about applying AI within a regulated enterprise.
- Committed to developing others and building sustainable team capability.