AI Product Manager

An AI Product Manager is a role connecting and intersecting business needs and robust AI and Data Science technologies, responsible for planning, validating and overseeing the implementation of AI products and solutions. This role focuses on guiding AI solutions end-to-end delivery to support business goals by matching relevant AI techniques with real-world business needs and expectations, foster ethical ways of data and AI consumption and application.

Key Responsibilities

Manage the entire product lifecycle, from planning, via execution, to delivery, upgrades and maintenance of AI-powered solutions and products, ensuring compliance with budget, scope, and project timelines. Manage product roadmap for AI-driven initiatives, prioritizing features where applications of GenAI/agents or other types of ML and DS techniques solve specific real-world business problems and generate tangible business value.

Make strategic decisions to balance business goals with technological capabilities. Conduct market and competition analysis to monitor and guide products’ positioning, and to identify opportunities for future AI applications. Act as the bridge layer between Tech AI teams and Business stakeholders. Support cross-disciplinary teams to develop AI applications that meet strategic business objectives.

Collaborate with Data Scientists and Engineers to define product specifications, while also working with customer-facing and market-focused teams to ensure the products resonate with the market. Foster strong relationships with key stakeholders and customers to establish continuous feedback loop and corresponding products upgrades flywheel.

Ensure AI solutions comply with privacy and ethical standards and industry regulations. Establish guidelines for responsible AI usage, unbiasedness and explainability, as well as data privacy management. Define and implement strategies and best practices for AI models evaluation and testing, and AI systems deployment, monitoring and maintenance.

Define AI-specific success metrics (such as false positive rate, precision, recall, latency, etc.) and correlate and track them with/alongside business KPIs. Facilitate creation and maintenance of proper product and tech documentation, specifications, Jira boards, user stories, etc. Contribute to AI Program Management team growth and development (e.

g. by participating in hiring process, by developing performance and training plans which are aligned with the company’s objectives and individuals career goals, by guiding the team, etc.)