IA Product Manager
BrazilFull-TimeManager
Salary not disclosed
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Job Details
- Required Skills
- Artificial IntelligenceData AnalysisSCRUMJiraAgile methodologiesRESTful APIsSaaSNotionPrompt EngineeringGenerative AI
Requirements
- Proven experience as a Product Manager in SaaS, e-commerce, or marketplace environments, with exposure to AI-driven or data-intensive products.
- Solid understanding of Generative AI (LLMs) and Predictive AI, including practical exposure to prompt engineering and fine-tuning concepts.
- Strong product discovery skills, including hypothesis validation, user research, and data-informed decision-making.
- Experience defining product vision, strategy, and roadmaps aligned with business objectives and measurable outcomes.
- Familiarity with agile methodologies (Scrum and/or Kanban) and tools such as Jira, Notion, and Miro.
- Strong communication skills, with the ability to translate complex technical topics into clear business narratives.
- Analytical mindset with focus on outcomes, prioritization, and continuous product improvement.
- Knowledge of APIs, integrations, and data analysis (bonus).
Responsibilities
- Lead the end-to-end lifecycle of AI-driven product initiatives, from discovery and hypothesis building to MVP delivery and continuous iteration, ensuring alignment with business strategy and customer needs.
- Define product vision and roadmap, translating complex business problems into scalable AI solutions using generative AI, predictive models, and agent-based systems.
- Collaborate with engineering, design, data, and business stakeholders to design workflows, interfaces, and technical requirements for AI-powered features.
- Drive experimentation with AI agents and new product concepts, validating hypotheses and identifying opportunities for new revenue streams.
- Monitor product performance through metrics and data analysis, identifying improvements and guiding prioritization decisions based on user value and impact.
- Act as the central point for AI product strategy, ensuring clear communication of progress, risks, and insights to leadership and cross-functional teams.
- Ensure proper documentation of product decisions, AI integrations, and discovery outputs to support scalability and knowledge transfer.
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