Palo Alto Networks interview notes, page 3 of 4

Large Enterprises

Most of these Palo Alto Networks write-ups come from Software Engineers (28), then Product Managers (2) and Backend Engineers (1). The most reported rounds are the technical phone screen (10), the system design round (8), the onsite coding round (4) and the product sense round (4).

31 interview notes · updated Sep 2026

Palo Alto Networks·Software Engineer·Onsite - System Design / Architecture

Jun 2026

System design round at Palo Alto Networks for a software engineer role. The whole thing revolved around one big streaming problem and they went deep on every layer of it.

You have an unbounded stream (list1) and a second list (list2) that may be too large to fit in memory. Design a system that outputs, in near real time, elements from the stream that are NOT present in list2. Cover ingestion, processing, storage, membership checks, Bloom filters, normalization, updates to list2, back-pressure, fault tolerance, scalability, and cost trade-offs.

“This was basically the entire interview.”

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Palo Alto Networks·Product Manager·Onsite - Product Sense / Strategy

Jun 2026

Product case interview at Palo Alto Networks, one question about launching a premium water brand. Pretty thin on details but the question itself had some meat to it.

How would you launch a high-end mineral water bottle into the market, given that it's positioned as a premium, pure-quality drinking water?

“I spent too long on the product itself and not enough on the go-to-market side.”

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Palo Alto Networks·Software Engineer·Technical Phone Screen

Jul 2026

Interviewed for a software engineer role at Palo and got a classic histogram problem. Nothing too surprising but the constraints were large enough that a naive O(n^2) solution would've timed out, so they clearly wanted the stack-based approach.

Given an array of non-negative integers representing bar heights in a histogram (each bar has width 1), find the largest rectangular area you can form using one or more consecutive bars. The rectangle's height is limited by the shortest bar in the chosen range.

“I knew this problem but still fumbled the stack logic under pressure.”

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Palo Alto Networks·Software Engineer·Technical Phone Screen

Jul 2026

Palo Alto Networks coding round for a software engineer role. Pretty standard greedy/two-pointer problem but the follow-up questions on distributed systems caught me a bit flat-footed.

You have an array of people's weights and a boat weight limit. Each boat holds at most two people. What's the minimum number of boats needed to carry everyone?
How would you handle this if the input array is too large to fit in memory on a single machine?
If multiple workers are processing parts of the input at the same time, how do you guarantee strong consistency in the final result?

“Classic greedy.”

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Palo Alto Networks·Product Manager·Onsite - Product Sense / Strategy

Jul 2026

Interviewed at Palo Alto Networks and got hit with a product strategy question about Apple and BlackBerry. Short post, one question, not much else to go on.

Why did Apple build the iPhone when BlackBerry was already dominant in the market?

“Classic disruption framing.”

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Palo Alto Networks·Software Engineer·Technical Phone Screen

Jul 2026

Interviewed for a software engineering role at Palo and got a greedy string problem involving placing water tanks on a street to cover adjacent houses. Classic minimize-the-count type question but with enough edge cases to trip you up if you're not careful.

You're given a string where 'H' is a house and '-' is an empty plot. A house is covered if a water tank is placed directly next to it (left or right). Tanks can only go on empty plots. Find the minimum number of tanks needed to cover every house, or return -1 if it's impossible.

“My first instinct was to scan left to right and greedily place a tank as far right as possible whenever I hit an uncovered house.”

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Palo Alto Networks·Software Engineer·Onsite - Coding / Algorithms

Jul 2026

Went through a coding round at Palo for a software engineer role. Three questions, all algorithmic, ranging from pretty standard to genuinely tricky. The expression evaluator one took me longer than I'd like to admit.

Given a sorted array of integers and a target value, find the index of the target. Return -1 if it's not there. Expected O(log n) time.
Design a data structure that supports insert, remove, and getRandom, all in average O(1) time.
Evaluate a math expression given as a string with +, -, *, / operators and non-negative integers. Operator precedence applies. Follow-up: support parentheses.

“Classic binary search, nothing to say really.”

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Palo Alto Networks·Software Engineer·Onsite - Coding / Algorithms

Jul 2026

Palo Alto Networks software engineer interview, coding round focused entirely on tree manipulation. Pretty standard algorithmic stuff but they pushed hard on complexity analysis and edge cases, which I wasn't fully prepared for.

Given a binary tree's root, mirror the tree by swapping every node's left and right children. Implement both a recursive and an iterative version, analyze time and space complexity for each, handle edge cases like an empty tree or a single node, and walk through a dry run on [5,3,8,null,4,7,9].

“I got the recursive version out pretty fast, base case plus swap plus recurse, no big deal.”

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Palo Alto Networks·Software Engineer·Technical Phone Screen

Jul 2026

Palo Alto Networks SWE interview with a fairly meaty algorithmic question that required more than just coding. They wanted the full picture: data structures, complexity, edge cases, the works.

Given two lists of strings, return all elements that appear in the first list but not the second, after normalizing both lists (e.g., lowercasing and trimming whitespace). Walk through your algorithm, data structure choices, duplicate handling, and time/space complexity.

“My first instinct was just to throw everything into a set and call it a day, but they kept pushing.”

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Palo Alto Networks·Software Engineer·Onsite - System Design / Architecture

Jul 2026

System design round at Palo for a software engineering role. The whole thing was one big open-ended question about designing a job scheduling and metrics platform on top of a Kubernetes-style infrastructure. Dense topic, lots of surface area to cover.

Design a cloud-native job scheduling and metrics monitoring platform for a Kubernetes-like environment, covering job submission APIs, scheduling logic with resource constraints, failure handling, and operational metrics with alerting.

“This thing sprawled fast.”

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