AI Product Manager

Kerry Consulting; Singapore; Presencial; SGD 120.000 - 190.000; Jornada completa

Descripción de la vacante

Kerry Consulting is seeking an experienced AI Product Manager to join a leading financial institution in Singapore. The role focuses on translating business challenges into scalable, production-ready AI products by bridging AI engineering, data science, and product management.

You will own the end-to-end AI product lifecycle from problem discovery and prototyping to deployment, adoption and continuous improvement, collaborating with stakeholders and AI/ML teams to deliver measurable business

Formación

• Proven experience in AI/ML solution development and AI product management.
• Hands-on technical background in data science, ML, or AI engineering.
• Strong ability to translate business requirements into product roadmaps.
• Experience collaborating with data scientists and AI engineers.

Responsabilidades

• Identify high-impact AI opportunities and translate them into product roadmaps.
• Lead hands-on solution discovery, rapid prototyping, and PoC development.
• Drive end-to-end AI product lifecycle from design to deployment and adoption.
• Ensure AI solutions meet security, governance, and scalability standards.

Conocimientos

AI product management

Python

Generative AI

LLMs

RAG

Stakeholder engagement

Prototype development

End-to-end product delivery

Herramientas

Generative AI frameworks

AI governance tools

Descripción del empleo

We are seeking an experienced AI Product Manager to join a leading financial institution, driving the development and deployment of AI solutions across business functions. This is a highly hands-on role at the intersection of AI engineering, data science, and product management, with a strong focus on translating business challenges into scalable, production-ready AI products.

This is an opportunity to work closely with business stakeholders and engineering teams in a forward-deployed capacity, taking ownership of AI solutions from problem discovery and prototyping through to implementation, adoption, and continuous improvement.

Responsibilities

You will work directly with business stakeholders to identify high-impact AI opportunities, understand operational workflows, and translate business requirements into technical solutions and product roadmaps. You will take a hands-on approach to solution discovery, rapid prototyping, and proof-of-concept development, working closely with data scientists and AI engineers to deliver production-ready AI applications.

You will drive the end-to-end AI product lifecycle, from use case prioritisation, solution design, and development through to deployment, performance monitoring, and user adoption. You will leverage Generative AI, LLMs, RAG, and agentic AI workflows to develop solutions that automate business processes, improve decision-making, and enhance operational efficiency.

You will act as a bridge between business and technology teams, balancing technical feasibility, business value, and product priorities while ensuring solutions meet enterprise standards for security, scalability, and AI governance.

Requirements

We are looking for an experienced AI Product Manager with a strong technical foundation in data science, machine learning, or AI engineering, having transitioned from a hands-on technical role into product management or AI solution delivery.

Proven experience in both AI/ML solution development and AI product management is essential. You should have practical experience with Python, machine learning, Generative AI, LLMs, RAG, or agentic AI frameworks, together with the ability to design, prototype, and deliver AI solutions.

Strong experience in product discovery, roadmap development, stakeholder engagement, and end-to-end product delivery is required. You should be comfortable working directly with business users, translating ambiguous problems into technical requirements, and collaborating closely with engineering teams to deliver measurable business outcomes.

Experience within financial services, banking, investment management, or financial technology, gained through in-house or consulting environments, will be highly relevant.

The successful candidate should combine hands-on technical depth, strong product ownership, and commercial acumen, with the ability to operate independently in a fast-paced environment and bridge the gap between business needs and AI engineering execution.