Adobe Software Engineer interviews, as candidates describe them, center on data structures and algorithms. Many also cover core CS, project deep-dives, and design discussions, followed by a hiring manager or HR conversation.
$165K
Avg. Base Comp
$215K
Avg. Total Comp
3-4 rounds
Typical Rounds
Not reported
Process Length
Candidates who interviewed for Adobe Software Engineer roles describe a process where data structures and algorithms carry the most weight, but rarely the whole loop. Reported coding problems include Subarray Sum Equals K, Wildcard Matching, and a simple Two Sum. Others are next greater element for each index and a design similar to an MRU queue that tracks the sum of the K most recently used elements. One candidate also had to mock an API call with pagination after two medium problems and found the time tight, so practice finishing cleanly under a clock.
Core CS questions appear often and tend to follow the team's stack. One candidate was asked about C++ static variables, delete[], and smart pointers, and another about Python OOP. An intern candidate was asked about overriding versus overloading, errors versus exceptions, and linked lists versus ArrayLists, plus databases and multithreading. In one loop, the hiring manager round covered designing a BST for a stream of integers and proving its complexity, followed by a producer-consumer pseudocode problem.
Design and specialty topics show up in different forms. One candidate was asked to scope a loosely defined end-to-end problem, state assumptions, and then discuss scalability. In another loop, the second technical round covered general machine learning and LLM topics instead.
Candidates who describe the final stage mention a hiring manager conversation about fit and how you work, though one found it highly technical. Reported round counts range from about three to four, and outcomes are mixed. Practice explaining your reasoning aloud, since a few candidates say interviewers valued the approach as much as the answer.
Synthesized from 76 candidate reports by our editorial team.
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Real interview reports from people who went through the Adobe process.
The loop at Adobe for this Software Engineer role had three rounds, and the coding bar was lower than I expected. Two of the rounds were technical. The first was a coding interview on a very simple Two Sum problem, the kind you'd see on LeetCode, so I'd make sure the basics are clean and move on. The second round was about machine learning in general. The questions covered LLMs and other ML topics, so this is where most of my preparation time should have gone.
The last round was with the hiring manager. It was meant to see whether I'd be a good fit for the team, so it was less of a technical test and more of a conversation about how I work.
I ended up declining the offer.
Prep tip from this candidate
Don't neglect LLM and general ML concepts even for a software engineering role, since one of the two technical rounds focused on them. The coding question itself was a simple Two Sum, so spend your time on the ML side.
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Synthesized from candidate reports. Individual experiences may vary.
Candidates report different entry points. Some describe a recruiter or HR call about the role and background, in one case with an easy SQL question and a coding problem. Others describe an online assessment mixing multiple-choice fundamentals with two coding problems. Experiences vary by team and level, so expect either to appear.
Candidates describe live coding rounds with LeetCode-style problems. Examples include Subarray Sum Equals K, Wildcard Matching, next greater element, and a simple Two Sum. One candidate had two medium questions plus an API pagination mock and found time tight. Interviewers expected clear explanations of your thinking.
Several candidates report OOP, operating systems, database, or multithreading questions alongside discussion of resume projects. Some rounds follow the team's stack, such as C++ internals, Python OOP, or ML and LLM topics in one case. Be ready to defend technical choices on your resume.
Some candidates describe design prompts. One was given a loosely scoped end-to-end problem followed by a scalability discussion, and an intern candidate mentions API and system design topics. Clarifying requirements and stating assumptions aloud may help.
Candidates report a final conversation with a hiring manager or HR that often focuses on team fit, past work, and soft skills. One candidate's manager round was instead deeply technical, covering BST design, smart pointers, and a producer-consumer problem.
