Product Manager - AI

We are looking for an experienced, highly autonomous Product Manager to own early-stage product development end-to-end: from discovery and validation to MVP launch, iteration, and scaling. The role is focused on an AI- powered social analytics / social intelligence product and requires a product leader who can combine customer discovery, product analytics, fast experimentation, technical understanding, and daily AI-enabled execution. This is not a coordination-only role. The right candidate must be able to personally create product artifacts, work with data, structure hypotheses, pressure-test AI-generated insights, and move from ambiguity to shipped outcomes without heavy supervision. What You Will Own Own the product lifecycle from opportunity discovery, problem framing, MVP definition, launch, analytics, iteration, and scale. Translate business goals and user problems into clear product hypotheses, scope, metrics, event tracking, user stories, and acceptance criteria. Build, test, and iterate MVPs rapidly using user feedback, funnel data, cohort behavior, competitive signals, and AI-assisted research. Define product vision, product strategy, success metrics, and prioritization logic for one or more product streams. Set up or specify product analytics: events, funnels, cohorts, activation metrics, retention metrics, experiment logic, and reporting needs. Work closely with engineering, design, marketing, sales, support, and leadership across a remote/distributed setup. Manage collaboration with outsourced and remote development teams, keeping scope, quality, timelines, and product decisions transparent. Use AI tools as part of daily product operations: discovery synthesis, competitor monitoring, PRD drafting, analytics exploration, QA support, prototype ideation, and productivity automation Several years in product management, preferably with early-stage B2C, prosumer SaaS, creator/social, analytics, martech, or intelligence products. Proven experience launching MVPs or new product features from zero, with clear hypotheses, metrics, user feedback loops, and post-launch decisions. Strong product analytics skills: event taxonomy, funnel analysis, cohorts, A/B testing, activation/retention metrics, and tracking requirements. Ability to manage several product tracks or experiments without losing clarity on priorities, owners, decisions, and business impact. Technical understanding strong enough to discuss APIs, data ingestion, tracking events, AI/LLM limitations, data quality, latency, edge cases, and implementation trade-offs. Experience working with remote, distributed, or outsourced engineering teams. Excellent written communication: clear PRDs, decision notes, experiment summaries, and stakeholder updates. High ownership, high autonomy, and comfort working in ambiguity without waiting for perfect inputs Opportunity to shape an early-stage product from the first strategic and operational layers. High autonomy and direct impact on product, user value, and business outcomes. Remote-friendly, international, distributed team environment. Culture focused on experimentation, measurable outcomes, documentation discipline, and AI-powered productivity. Exposure to both B2C and B2B product challenges as the product and portfolio evolve.