iOS Developer Interviews Score Lower Than Software Engineer. The Data Shows Why.
Most candidates preparing for tech interviews assume Software Engineer roles have the hardest interview process. The data from Final Round AI's Interview Copilot, which captures live interview sessions across multiple companies and roles, tells a different story.
Final Round AI analyzed 83,421 live interview session records across 14 standardized tech roles from October 2022 to September 2025. The metric is a 0-to-100 score measuring how complete and well-structured candidates' answers were during actual job interviews.
iOS Developer averaged 50.6. Software Engineer averaged 54.3. Product Manager averaged 59.0.
The Full Role Ranking
From lowest to highest average answer score:
- iOS Developer: 50.6 (413 sessions)
- Engineering Manager: 53.0 (525 sessions)
- Site Reliability Engineer: 53.9 (1,736 sessions)
- Software Engineer: 54.3 (20,955 sessions)
- Data Analyst: 54.5 (4,466 sessions)
- QA Engineer: 54.8 (5,753 sessions)
- Security Engineer: 55.3 (4,255 sessions)
- Data Engineer: 55.4 (14,201 sessions)
- DevOps Engineer: 55.5 (13,740 sessions)
- Machine Learning Engineer: 56.7 (1,861 sessions)
- Data Scientist: 57.8 (4,676 sessions)
- Cloud Engineer: 58.1 (889 sessions)
- Product Manager: 59.0 (2,814 sessions)
The dataset average across all 14 roles is 55.3.
Why iOS Developer Scores So Low
iOS interview questions require deep knowledge of Swift, UIKit, SwiftUI, and Apple-specific frameworks. Candidates who prepare with general software engineering resources (LeetCode, system design guides) arrive under-prepared for that platform-specific depth. The gap between general SWE prep and iOS-specific prep is the primary driver of the 50.6 average.
This is not an abstract difficulty gap. In live sessions, the questions that produce the lowest iOS scores are not algorithmic puzzles but platform-specific ones: how UIKit manages view lifecycle, how Grand Central Dispatch handles concurrency, how SwiftUI state propagates through a view hierarchy. Standard prep guides do not address these in depth.
Why Product Manager Scores Highest
Product Manager at 59.0 contradicts the common narrative that PM interviews are among the most difficult. PM candidates give more complete, better-structured answers than any other role in the dataset.
The explanation is preparation ecosystem quality. Amazon's Leadership Principles have an entire prep industry built around them. Google's STAR-format behavioral questions have thousands of documented candidate examples. PM candidates use frameworks like CIRCLES and STAR that structure their answers specifically for the questions asked. The 59.0 score reflects better preparation alignment, not easier interviews.
Software Engineer Scores Are Declining
Software Engineer averaged 55.6 in 2023, 54.5 in 2024, and 53.0 in 2025. That 2.6-point decline across three years is the most significant trend in the role dataset.
Two factors likely contribute. First, the technical bar at top companies (Amazon, Google, Meta) has increased since 2023. Behavioral rounds require more specific, measurable outcomes in STAR answers. Second, more candidates are using Interview Copilot in live sessions without prior structured preparation, pulling the average down.
Data Engineer, by contrast, stayed consistent at 55.3 to 55.9 across the same three years. The prep ecosystem for Data Engineering has stabilized around SQL, data pipeline design, and cloud infrastructure questions.
What This Means for How You Prep
For iOS Developer candidates: build at least two iOS-specific projects you can walk through in full architectural detail. Focus prep on Swift-specific language features and Apple framework patterns, not only general algorithms.
For Software Engineer candidates: the 2023-to-2025 decline suggests behavioral prep is now as important as LeetCode prep. If you are targeting Amazon, Google, or Meta, your STAR answers need specific, quantified outcomes, not general team contributions.
For Engineering Manager candidates: the 53.0 score reflects a gap specifically in how EM candidates answer leadership and conflict-resolution questions. The behavioral dimension of EM interviews is where most candidates score lowest, not the technical one.
The full dataset with charts breaking down all 14 roles is in Final Round AI's research report: https://www.finalroundai.com/blog/tech-role-interview-difficulty-data
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