Job Description & Details
This is a heavy-hitting product leadership role where you will not just manage a backlog, but genuinely define the AI roadmap from scratch. If you're tired of feature-factory product gigs and want to build actual Agentic AI systems that drive business automation, this is worth a close look.
What You'll Actually Be Doing
You will spend your days bridging the gap between raw business requirements and complex Generative AI capabilities. Expect to spend significant time collaborating with engineering leads to figure out technical feasibility, defining experimentation frameworks, and ensuring that whatever autonomous agents you ship actually adhere to strict data privacy and Responsible AI guidelines. You'll own the product vision end-to-end, meaning you take the heat if the metrics don't move.
The Core Tech Stack
You need deep familiarity with the GenAI landscape, specifically around Agentic AI workflows, LLM orchestration, and automation tooling. The team relies on your ability to understand API constraints, prompt engineering paradigms, and the underlying risks of deploying probabilistic models into deterministic business processes.
Interview Expectations
Expect the hiring manager to throw a curveball scenario where an autonomous agent goes rogue or hallucinations mess up a critical customer workflow; they want to see how you balance rapid innovation with strict safety guardrails. You'll also likely get grilled on your prioritization frameworkâbe ready to explain a time you had to kill a cool AI feature because the ROI or risk profile didn't make mathematical sense.
Application Advice
Skip the generic product management buzzwords and heavily emphasize your direct experience shipping AI-powered features, particularly anything involving agents or multi-step LLM chains. Make sure terms like 'Responsible AI', 'experimentation frameworks', and 'value realization' are explicitly woven into your experience section so you can clear the initial ATS screening easily.