AI Product Manager

Role & responsibilities

• Define the AI product vision, strategy, roadmap, and long-term business objectives.
• Identify and prioritise AI use cases based on customer needs, market opportunities, business value, and technical feasibility.
• Collaborate with engineering, data science, design, and business teams to develop and launch AI-powered products.
• Translate customer requirements and business problems into product specifications, user stories, and acceptance criteria.
• Evaluate Generative AI models, LLMs, RAG architectures, and AI agents for suitable product applications.
• Manage the end-to-end product lifecycle, from discovery and prototyping to launch, monitoring, and continuous improvement.
• Define and track product KPIs, adoption, engagement, customer satisfaction, accuracy, and return on investment.
• Conduct market research, competitor analysis, customer interviews, and product experiments to validate opportunities.
• Establish AI evaluation frameworks to monitor model quality, reliability, hallucinations, latency, and cost.
• Ensure AI products comply with data privacy, security, ethical AI, and applicable regulatory requirements.
• Develop go-to-market strategies and collaborate with sales, marketing, and customer success teams.
• Communicate product priorities, progress, risks, and business outcomes to stakeholders and senior leadership.

Preferred candidate profile

• Bachelor's degree in Computer Science, Engineering, Information Technology, Data Science, Business Administration, or a related discipline.
• MBA or postgraduate qualification in Product Management, Business Analytics, or Strategy preferred but not mandatory.
• 5 to 10 years of experience in product management, technology, business analysis, or related roles, with experience delivering AI-powered products preferred.
• Strong understanding of Generative AI, LLMs, prompt engineering, RAG, AI agents, machine learning fundamentals, and AI product use cases.
• Experience with product roadmaps, prioritisation frameworks, Agile methodologies, product discovery, and lifecycle management.
• Proficiency in product analytics, SQL, KPI tracking, experimentation, and data-driven decision-making.
• Ability to collaborate effectively with engineering, data science, UX/UI, and business teams.
• Understanding of AI evaluation, model limitations, hallucination mitigation, responsible AI, data privacy, and security.
• Familiarity with cloud AI platforms, APIs, and AI development tools is an advantage.
• Strong customer-centric mindset with the ability to translate complex technical concepts into business value.
• Excellent communication, strategic thinking, problem-solving, stakeholder management, and leadership skills.
• Demonstrated ability to launch successful products, drive adoption, and deliver measurable business outcomes.