Azoma is a hypergrowth company defining the agentic commerce category. Our revenue has grown tenfold over the past year, and we now work with 20 of the world’s 50 largest CPG companies, alongside other enterprise customers.
We’re building the merchant-side infrastructure for the era of personal shopping agents - transforming how brands and retailers work with AI agents that discover, evaluate and purchase products on behalf of consumers.
Our team combines advanced AI, software engineering and deep commerce expertise. Joining Azoma means taking hands-on ownership as we scale, shaping products used by global brands and helping define how commerce works in the age of AI.
This role spends roughly 70% of its time in customer interviews, 10% creating mockups and 20% working with engineers on prototypes and product experiments.
What you will do
- Recruit and interview users, budget owners and potential buyers. Examine recent work, existing spending, workarounds and purchasing decisions.
- Trace promising problems across customers and segments: identify who experiences the pain, who controls budget, what triggers a purchase and what could prevent adoption.
- Produce clear opportunity briefs with customer evidence, commercial assumptions and unresolved questions; recommend what to test, pursue or stop, including evidence against your preferred idea.
- Scope prototypes with engineers, define learning goals and decision thresholds, and recruit pilot partners whose time, data or budget commitments provide credible evidence of demand.
Skills and experience
- You have personally explored and validated a new B2B product or substantial product expansion, with evidence that customer learning changed what the team chose to build.
- Excellent interviewing, listening and synthesis. You can get beyond feature suggestions to actual behavior, operational costs, organizational constraints and the consequences of leaving a problem unresolved.
- Commercial understanding of enterprise buying: you know how to distinguish an interested user from a viable buyer and test spending priorities, approval processes and willingness to commit.
- Practical UX skills to make your own mockups, plus enough technical fluency to discuss data access, integration requirements and prototype scope with engineers.
- Strong experimental judgment and clear writing. You can identify the riskiest assumption, choose a fast way to test it and explain why evidence supports continuing or stopping.
