AI Solutions Manager

We are seeking an experienced AI Product Manager to lead the strategy, roadmap, and execution of AI-powered products. This role requires a deep understanding of AI/ML applications, user behaviour, and market dynamics, combined with the ability to collaborate across global and regional teams. While product management will be the core responsibility, technical/architectural knowledge will be considered a strong plus.

Key Responsibilities

Product Strategy & Roadmap

• Own the AI product strategy and roadmap, ensuring alignment with company-wide goals.
• Identify opportunities to embed AI/ML capabilities across features, UI/UX, personalization, automation, payments, and customer experience.
• Prioritise initiatives based on business impact, user value, and technical feasibility.

User & Market Understanding

• Deeply understand user behaviour, cultural nuances, and commercial dynamics through research, data insights, and market analysis.
• Act as the voice of users, advocating for their needs and preferences in product development.
• Ensure AI products are built with ethical, explainable, and responsible practices.

Product Development & Execution

• Collaborate cross-functionally with engineering, research, design, and global/regional teams to define, build, test, and launch high-impact features.
• Drive the end-to-end product lifecycle — from ideation to rollout, measuring success, and iterating based on feedback.
• Combine big-picture thinking with hands-on execution, and step into the details when needed.

Qualifications

Must-Have

• 4-5 years of product management experience, including ownership of product strategy and execution in cross-functional settings.
• Proven experience in AI products, with a strong understanding of user behaviour and market dynamics.
• Strong understanding of AI/ML concepts, data-driven product development, and user engagement strategies.
• Excellent communication and leadership skills with the ability to build alignment across global teams.
• Demonstrated ability to thrive in ambiguous environments, solve hard problems, and approach decisions with a first-principles mindset.

Good-to-Have (Technical/Architectural Knowledge)

• Familiarity with software/system architecture, APIs, and cloud infrastructure.
• Exposure to scalable AI systems, MLOps, and distributed computing.
• Understanding of data engineering, microservices, and DevOps practices.