Stitch.co Product Manager Interview Experience
Stitch.co · Staff
Interview process
Communication was really easy. Felt like they really wanted to speak to me and were very patient and attentive
Interview rounds · 3
- 1
Recruiter screen
- Q1. About your background: whether you had actually built LMS/core banking systems before.
- Q2. About your experience: whether you had done work in areas like calculation integrity / related implementation challenges before.
- 2
Technical round
- Q1. How would AI fit even into the first layer of a deterministic decisioning workflow?
- Q2. Where do you think Stitch can add value for banks?
- Q3. Can AI be used alongside existing human and rules-based processes rather than replacing them immediately?
- Q4. Do you have hands-on experience with workflow automation platforms and BPMN-style systems?
- Q5. How deep is your experience with ML models?
- Q6. Can you give a concrete example of an ML product you worked on that had real business impact?
- Q7. Have you worked on API design as a product?
- Q8. How do you think about API structure and the tradeoff between too many APIs vs overly complex ones?
- Q9. How do you think about object design/modeling in systems like this?
- Q10. What information should be exposed externally vs kept internal in APIs?
- 3
Final / onsite round
- Q1. How would you approach making a deterministic workflow system more configurable and AI-enabled?
- Q2. Where would you start introducing AI in such a workflow product?
- Q3. How would you decide whether a new configurable/AI workflow capability is worth building?
- Q4. Do you see yourself contributing only in implementation with clients, or also to the core product itself?
- Q5. Which product area would you pilot first, and which would you avoid at the start?
Tips from the candidate
What interviewer was testing:
- Product judgment for workflow/AI platforms— where to add AI, where not to.
- Ability to turn vague customer pain into product scope — client first, use case first, success metric first.
-Platform thinking — APIs, object model, configurability, exposure vs internal logic.
-Credibility on AI/ML — not theory, but where it works in production and how to evaluate it.
-Founder/startup fit — why Stitch, why now, why you, and whether you can help shape product rather than only implement.
Company culture
Very bright and extremely smart people, scientist vibes