About Cozmo AI
Cozmo AI builds AI Employees who can speak, think, and do.
We help enterprises deploy voice-native AI teammates that drive revenue across sales, support, and collections replacing costly human workflows with intelligent, always-on agents.
Backed by Y Combinator, Goodwater Capital, and Dubai Future District Fund, we’ve reached $1.5 M ARR in < 6 months, and are scaling from $1.5 M → $10 M ARR in 12 months.
The Role
We’re looking for a Product Manager who lives at the intersection of data and behavior — someone who can read dashboards like a scientist but think like a storyteller.
You’ll own the full cycle of how our customers use Cozmo AI — from activation to expansion — translating raw usage data and client feedback into product decisions that drive retention, stickiness, and growth.
What You’ll Do
- Own product analytics: Define, instrument, and interpret key metrics (activation, retention, usage depth, workflow success rates, etc.).
- Turn data → insight → action: Identify behavioral patterns that separate power users from casual ones, and design experiments to replicate success.
- Collaborate deeply: Work with Engineering, Design, and Forward-Deployed Teams to improve agent UX, dashboard usability, and enterprise integrations.
- Close the loop: Partner with Customer Success to gather qualitative insights from live deployments and use them to prioritize roadmap items.
- Drive impact: Champion data-informed decisions that make our AI employees more intelligent, contextual, and effective over time.
You Should Have
- 1 + years of PM or product-data hybrid experience in B2B SaaS / AI / voice tech.
- Strong command of analytics tools (Mixpanel, Amplitude, Looker Studio, SQL, or equivalent).
- Obsession with understanding why users behave a certain way, not just what they do.
- Ability to communicate complex insights clearly to executives, engineers, and customers alike.
- Bonus points for experience in LLM / voice AI / workflow automation / CRM integrations.
- Bonus if you have a problem solving background.
Why Join Us
- Be part of a category-defining company that’s rewriting how enterprises work.
- High-ownership culture: zero bureaucracy, full accountability, rapid execution.
- Competitive salary, meaningful equity, and global impact.
🚀 Y Combinator Company Info
Y Combinator Batch: W22
Team Size: 11 employees
Industry: B2B Software and Services
Company Description: We help you build AI Employee who can speak, think and do
💰 Compensation
Salary Range: $100,000 - $200,000
Equity Range: 0.5% - 2.0%
📋 Job Details
Job Type: Full-time
Experience Level: 1+ years
Time to Hire: 15
🛠️ Required Skills
Data Modeling Data Analytics
🎯 Interview Process
### **Stage 1: Founder Screen (30–45 min)**
Led by: Alok (CEO) or Nuha (CTO)
Goal: Assess mindset, clarity of thinking, and cultural alignment.
What we’re looking for:
- First-principles thinking and speed of reasoning
- Curiosity about data and user behavior
- Ability to link product improvements to business impact
- Communication clarity and founder-level ownership
Stage 2: Product Deep Dive Assignment (48–72 hours)
Goal: Evaluate analytical skill, prioritization, and storytelling.
Format: Case study (you’ll receive real anonymized product usage data or feature snapshot).
Deliverable:
A short deck (max 5 slides) answering:
- What’s working and what’s not in the usage data?
- Which user behaviors predict activation or drop-off?
- What 2 product changes would you make to improve retention or monetization, and why?
- Optional: How would you validate these hypotheses with experiments?
Stage 3: Product & Data Systems Interview (60 min)
Led by: Engineering Lead + Product Analyst
Goal: Understand technical fluency and product depth.
What we assess:
- Comfort with analytics tools (Mixpanel, SQL, Amplitude, etc.)
- How you think about instrumentation, funnel setup, and event taxonomy
- Understanding of AI product feedback loops and usage telemetry
Stage 4: Culture + Execution Fit (30–45 min)
Led by: Founders / FDT Head
Goal: Evaluate bias for action, adaptability, and Cozmo culture fit.
Signals:
- Strong ownership mindset (moves fast without waiting for perfect data)
- Comfort in ambiguity
- Obsessed with results and iteration
- Can thrive in high-speed “war mode” environment
Outcome: Final round → offer discussion within 24–48 hours.