idankars · (hybrid) · full-time
idankars is a technology company building at the intersection of AI and product innovation. While the specifics of their product portfolio are best described by the team directly, the company is actively investing in AI capabilities — evidenced by a dedicated AI Product function within their organization. If you're drawn to companies where AI is a core part of the product strategy rather than an afterthought, idankars is worth a closer look.
The Product team here operates with clear ownership: roadmaps are driven by data, decisions are made cross-functionally, and AI/ML is treated as a first-class product discipline. This is a company building something that requires people who can sit comfortably at the boundary of technical possibility and user need. As a Mid AI Product Manager at idankars, you'll own the end-to-end product lifecycle for one or more AI-powered product surfaces. That means starting from user and business problems, translating them into clear product requirements, and working shoulder-to-shoulder with engineering, data science, and design to ship solutions that actually work in production — not just in demos.
This role sits at the center of a cross-functional system. You'll be the connective tissue between data science teams building models and the customers and stakeholders who need those models to do something meaningful. You'll set the roadmap, prioritize ruthlessly, and make tradeoffs that balance model performance, user experience, and business outcomes.
Success in this role looks like shipping AI features with measurable impact, earning deep trust from your engineering and data science counterparts, and building a roadmap that the rest of the company rallies behind. You'll be expected to go deep enough on the technical side to have credible conversations with ML engineers, and broad enough on the business side to represent user needs without losing the thread.
Shape AI-powered product strategy at idankars — owning roadmap, driving cross-functional alignment, and turning ML capabilities into measurable user impact.