The role owns features end to end, from spotting a problem through launch and measuring results, so a strong candidate brings a track record of running that full cycle. It also calls for enough technical depth to work closely with engineers and designers, plus the judgment to weigh impact, feasibility and business value when prioritizing. Clear communication and comfort working independently matter, since the person leads discovery and iterates on solutions in an agile setup.

How it fits the AI era

AI is treated as a working tool here, used for research, analysis, prototyping and speeding up everyday workflows, so the role expects regular hands on use rather than curiosity alone. What stays human is the judgment side: understanding customer needs, choosing what to build, and deciding how success gets measured. The job sits where AI assists the product process but does not replace the thinking behind it.

How it builds AI experience





A candidate would gain practical experience applying AI across discovery and prototyping inside a B2B software company serving IT teams. Building on that, familiarity with chatbots, virtual agents, conversational platforms or large language models would be valued, as would comfort with terminals, APIs or low code tools for research and prototyping. Those skills can be developed by using AI tools regularly on real product work and learning how conversational products are put together.

Worth showing

- Full product lifecycle ownership
- Technical collaboration with engineering
- Regular AI tool use
- B2B or SaaS background
- Metrics and prioritization

This is our own read, written from the employer's posting and the company's Spotlight. The employer's posting is the source of truth for the role.

About InvGate

InvGate provides IT Service Management and IT Asset Management software that helps organizations streamline service operations, optimize IT spend, and manage asset lifecycles, per the company.

📌 Product Manager (Buenos Aires)
🏢 present of AI
📍 Buenos Aires