Product Manager - AI

Job Description

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

Requirements

• 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

Benefits

• 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.