PRODUCT MANAGER - PLATFORM GROWTH & SCALING

Centific is a frontier AI data foundry that empowers enterprise clients with scalable AI deployment. The Product Manager will design and ship a social platform, stabilizing existing architecture and leading the development of a contributor marketplace, aimed at enhancing engagement and scaling user participation.

Responsibilities:

• Own the contributor onboarding redesign: reduce sign-up-to-first-task from 30 minutes to under 3 minutes by simplifying identity verification, certification, and task matching
• Work directly with engineering on legacy architecture decisions — understand data flows, surface tradeoffs, and advocate for solutions without requiring engineering to translate for you
• Define and track platform health metrics: activation rate, time-to-first-task, task completion rate, payment cycle time, contributor satisfaction score
• Establish a fast feedback cadence with engineering: review shipped features in dev environments, provide same-day input, reduce sprint cycle drag
• Design and own the algorithmic task feed: a personalized interface where contributors discover tasks, micro-learning content, and peer activity matched to their skills and history
• Build the contributor identity layer: public AI expertise profiles with verified accuracy rates, domain certifications, skill badges, and shareable portfolio artifacts
• Design PLG growth loops: content share mechanics, peer validation referral bonuses, and cohort-based project matching to drive organic contributor acquisition
• Lead gamification systems: streaks, tier progression, leaderboards, and certification unlocks designed to drive daily return behavior, not just one-time activation
• Collaborate with data science on the matching and recommendation engine: contributor-to-task routing, dynamic pricing, and cold-start solutions for new contributor segments
• Partner with AVP of Product to define the roadmap balancing stabilization, growth, and enterprise B2B requirements
• Work with enterprise sales to translate client requirements — specialized contributor segments, domain certifications, rapid turnaround SLAs — into platform capabilities
• Define North Star metrics across both sides of the platform: DAU/WAU, session depth, task completion rate, data pipeline volume, match accuracy
• Build and mentor product success team members as the function grows

Requirements:

• 5–8 years of product management experience in consumer platforms, marketplace products, or growth-focused roles
• Proven track record designing and shipping growth loops with measurable activation, retention, or referral outcomes — not just funnel optimization
• Experience with two-sided or multi-sided marketplace dynamics: contributor/creator activation, supply/demand balancing, liquidity mechanics
• Hands-on experimentation: A/B test design, holdout groups, guardrail metrics, statistical significance — owning the full cycle from hypothesis to roadmap decision
• Experience working with distributed engineering teams across timezones: able to communicate requirements precisely in async formats and maintain momentum without synchronous dependency
• SQL proficiency: writes and interprets queries independently for funnel analysis, cohort breakdowns, and experiment readout
• Comfortable navigating codebases and using AI coding tools (Claude Code, Cursor, Copilot) to demo features, review shipped work, and reduce discovery dependency on engineering
• Working knowledge of APIs, data flows, and system architecture — able to identify where technical debt creates product risk and communicate tradeoffs clearly to engineering leadership
• Able to participate in ML/data science discussions on model inputs, signal design, and experiment methodology — not required to build models, but required to spec and evaluate them
• PLG & viral mechanics: designs referral loops, social sharing triggers, and network-driven onboarding — not just onboarding checklists
• Gamification: experience with streak mechanics, badge systems, tier progression, or engagement loops that drive habitual return behavior
• Bias to action: ships MVPs quickly, iterates on real signal, comfortable with ambiguity and incomplete data
• User-centric: obsessed with understanding contributor pain points and behavior — goes through the product as a user, not just as a PM reviewing specs
• Collaborative: builds trust with engineering, data science, operations, and sales — operates as a connector, not a gatekeeper
• Experience owning an algorithmic content feed, recommendation system, or personalization engine as a PM — able to engage with ranking logic, signal weighting, and cold-start problems (strong preference, not hard requirement)
• Background at a high-scale consumer social platform, creator economy product, or content feed with large active user bases (strong preference, not hard requirement)
• Experience with creator identity, professional credentialing, or reputation systems
• Background in AI/ML product development: worked on products where ML models are a core feature, not just a backend tool
• 0-to-1 platform launches with demonstrated user growth
• Experience with gig economy, crowdsourcing, or workforce platforms
• Mandarin Chinese: significant practical advantage given our China-based engineering team
• International/global product experience across multiple markets and languages