AI Product Manager

About the Company

idankars appears to be a technology company operating in the product and software space, likely serving business or consumer markets given the investment in a dedicated R&D function. With an AI Product Manager role sitting inside R&D, the organization seems to be building AI and ML capabilities as a core part of its product strategy rather than bolting them on. The hybrid work model and mid-level hire suggest a company with enough structure to support embedded teams but still room for this role to shape how AI products are defined and delivered. If you're drawn to companies where R&D work translates directly into shipped product, idankars appears to be building in that direction.

About the Role

This is a role for a product manager who has already done the hard work of shipping an AI-powered product and wants to go deeper — owning the full lifecycle of intelligent features inside an R&D environment where the problems are genuinely unsolved. You'll sit at the intersection of research and delivery, turning ambiguous signals into executable roadmaps and making sure the right things get built, measured, and improved. The impact here is direct: what you define and prioritize shapes what idankars ships next.

Responsibilities

• Own the end-to-end product lifecycle for AI-powered features — from discovery and scoping through launch and post-release iteration — ensuring each release moves the needle on user and business outcomes.
• Translate messy, ambiguous problems into crisp product requirements that data scientists and ML engineers can act on, reducing back-and-forth and keeping research cycles focused.
• Define the metrics that matter for AI features before they ship, then track and analyze them post-launch to drive prioritization decisions grounded in evidence rather than instinct.
• Partner directly with ML engineers and data scientists on a daily basis, helping the team navigate model constraints, manage probabilistic outputs, and set realistic expectations across stakeholders.
• Build and maintain the product roadmap for your AI domain, making trade-offs explicit and communicating prioritization rationale clearly to R&D leadership and cross-functional partners.
• Continuously assess the problem space through user research, competitive signals, and data, feeding insights back into the discovery process to keep the team working on the highest-value problems.

What we're looking for

• Has shipped at least one AI or ML-powered product end-to-end — you've navigated discovery, scoping, launch, and iteration on a system where the outputs weren't deterministic, and you can speak to what you learned.
• Has turned ambiguous user and business problems into clear, actionable product requirements that a research or engineering team could execute against without constant clarification.
• Has defined meaningful success metrics for AI features up front and used data post-launch to make real prioritization calls — not just reported numbers, but acted on them.
• Has worked directly alongside data scientists or ML engineers and built the credibility to have honest conversations about what a model can and can't do, and when a probabilistic result is good enough.
• Demonstrates strong written and verbal communication — able to align stakeholders around a product direction even when the underlying technology is complex or the timeline is uncertain.
• Shows a track record of making prioritization decisions under constraints, balancing research ambition with delivery reality.

Nice to have

• Has operated inside an R&D or innovation team where outputs are exploratory and timelines shift — and knows how to keep a product vision coherent through that uncertainty.
• Has experience explaining AI capabilities and limitations to non-technical audiences, whether customers, executives, or go-to-market teams, without overselling or underselling what the system does.
• Has led or contributed to build-vs-buy evaluations — prototyping tools, assessing vendors, and synthesizing findings into a recommendation the team could act on.
• Has contributed to responsible AI practices, model governance, or fairness reviews as part of the product development process.

Benefits

• Competitive base salary benchmarked to mid-level product roles in the technology sector, with performance-based upside.
• Hybrid work model that gives you meaningful in-person collaboration without a rigid five-day-a-week commute.
• Direct access to R&D leadership and a seat at the table where product and research strategy gets shaped — not a role that executes someone else's roadmap.
• Dedicated budget for professional development, including conferences, courses, and tools relevant to AI product management.
• Collaborative team environment where your prioritization decisions and product instincts are trusted and acted on.
• Opportunity to grow into a senior product leadership track as idankars scales its AI capabilities.