Product Manager (Native AI Products & New Ventures)

Explore New Opportunities: Scan the AI and data landscape continuously—talking to customers, studying competitors, following research—to identify where Oxylabs can create genuinely new value with AI.

Own the 0-to-1 Journey: Define, prototype, and validate new AI-native product concepts from early hypothesis to first paying customers. Move fast, kill what doesn't work, double down on what does.

Drive AI Product Strategy: Develop a clear point of view on how large language models, AI agents, and intelligent automation can be built into Oxylabs' products—and make the case internally to invest in the right bets.

Partner Engineering: Work alongside product engineers to design AI product experiences, define evaluation criteria, and ship production-ready AI features.

Shape the Customer Experience: Ensure that AI capabilities aren't just technically impressive—they solve real user problems in ways people want to use. Champion simplicity and clarity in AI product design.

Build Internal Conviction: Communicate clearly about uncertainty, trade-offs, and early signals. Help leadership and stakeholders make confident bets in a fast-changing environment.

Experience: 2+ years in product management, with meaningful experience building new products—ideally including at least one 0-to-1 or early-stage product launch.

AI Product Fluency: Deep familiarity with the current AI landscape—LLMs, AI agents, embedding models, RAGs, MCPs, and how these technologies translate into real product value (not just demos).

Entrepreneurial Drive: Comfort operating with significant ambiguity. You know how to make progress when there's no roadmap, no clear answer, and no established playbook.

Customer Discovery: Strong discovery and validation skills—able to distinguish real customer problems from stated preferences and design experiments to test assumptions cheaply and quickly.

Product Instinct: A strong intuition for what makes AI products feel magical versus frustrating, and the judgment to make the right call without waiting for perfect data.

Communication: Able to build internal alignment around uncertain bets, write compelling product narratives, and explain complex AI concepts to non-technical stakeholders.

Mindset: High resilience, low ego, and a genuine love for learning in fast-moving, ambiguous environments.

Hands-on experience building or shipping AI-native products (copilots, agents, AI search, intelligent data tools, etc.).

Familiarity with web data, crawling infrastructure, or data extraction as a domain.

Experience at an early-stage startup or within a new ventures / innovation team inside a larger company.

Background working with ML teams on model evaluation, prompt engineering, or AI product QA.