Palo Alto Networks Product Manager Interview Experience
Palo Alto Networks · Senior
Interview process
The overall process was too long. Reached out by the recruiter at the end of May, Hiring manager screening at the beginning of June, then being ghosted for almost a month, got recruiter's email for the next round, which is a take home assignment (AI prototype). Presented my prototype with hiring manager and a SW engineer at the beginning of July, and complete 4 final rounds at the end of July. Added one additional round for technical at the beginning of August, and ghosted by the recruiter again. I heard from another recruiter that the roles was filled so I assumed I was rejected. Most of the interviews are just like the typical PM interview, no PM case except for the AI prototype assignment. I didn't do well on the technical and the skip level interview. The skip level interview was suppose to be a cultural fit interview but it turned out to be a technical interview so caught me off-guard. All technical interviews (+ the skip level one) asked deep technical question.
Interview rounds · 5
- 1
Recruiter screen
Behavioral- Q1. Tell me about yourself.
- Q2. Tell me about your past projects.
- 2
Phone screen
- Q1. Tell me about your past projects.
- 3
Take-home assignment
Product DesignProduct Strategy- Q1. Using AI to build a knowledge agent prototype
- 4
Technical round
Product Strategy- Q1. How would you build any product using Gen AI?
- Q2. What's the backend architecture of the AI product you built?
- Q3. How do you reduce false-negative/false-positive cases in an AI product?
- Q4. how does the Knowledge agent work? (focus on backend)
- 5
Final / onsite round
BehavioralProduct Strategy- Q1. How do you work within a cross-functional team?
- Q2. Walk me through the backend architecture of AI product.
- Q3. If the adoption of an AI product is low, how would you fix it?
- Q4. How do you prioritize product requirements?
Tips from the candidate
I didn't expect to have such a deep technical interview with the company. Be prepared. for questions such as:
1. Tell me about AI. How does the backend work?
2. If you are building AI tools to collect knowledge across the whole company, how do you build it? How does the backend look like? (go really technical)
3. If you have two tables, account table (with account ID) and sales table (account ID, selling date, amount), how do you build dashboard to show yearly sales amount for each account ID using SQL/ Python?
Company culture
I think what attracted me is that the company was really early to adopt AI tools (in 2023 Sep), and emphasized on AI for most of the workflows.