How to Crack AON Coding Interviews in 2026

AON’s technical interviews for software engineering roles are designed to assess problem-solving, coding proficiency, and the ability to think under pressure. The process typically involves one or more coding rounds focusing on algorithmic challenges, often conducted on platforms like HackerRank or through a live collaborative editor. Success hinges on a clear understanding of their favored topics and a structured, efficient preparation strategy.

By the Numbers — Difficulty Breakdown and What It Means

Based on recent patterns, AON's coding interviews can be broken down into four questions with a clear distribution: two Easy (50%), one Medium (25%), and one Hard (25%). This structure is critical for your strategy.

The two Easy questions are your foundation. They test basic coding fluency and logical thinking. Failing to solve these quickly and cleanly can be a significant red flag. The Medium question is the differentiator; it often requires applying a known algorithm or pattern to a slightly novel scenario. The single Hard question is the gatekeeper. It’s not necessarily about finding the perfect optimal solution under time pressure, but about demonstrating systematic problem-solving—discussing trade-offs, starting with a brute force approach, and logically optimizing from there. Your goal should be to ace the Easy and Medium questions confidently, leaving maximum time to tackle the Hard problem with a clear, communicated thought process.

Top Topics to Focus On

The most frequent topics in AON's interviews are Array, Bit Manipulation, and Greedy algorithms. Mastering these areas is non-negotiable.

Array problems are ubiquitous. You must be proficient in techniques like two-pointers, sliding window, and prefix sums. The ability to manipulate indices and traverse arrays efficiently is fundamental.

Bit Manipulation questions test your understanding of binary representations and low-level operations. Key patterns include checking, setting, toggling bits, and using XOR for clever solutions (like finding a unique number).

Greedy algorithms involve making the locally optimal choice at each step to reach a global optimum. These problems often require proving that the greedy choice is valid, so focus on classic problems like interval scheduling or coin change (when applicable).

For Arrays, the Sliding Window pattern is essential for problems involving subarrays with constraints. Here’s a classic example: finding the maximum sum of any contiguous subarray of size k.

def max_sum_subarray(arr, k):
    if len(arr) < k:
        return None
    window_sum = sum(arr[:k])
    max_sum = window_sum

    for i in range(k, len(arr)):
        window_sum = window_sum - arr[i - k] + arr[i]
        max_sum = max(max_sum, window_sum)
    return max_sum

Preparation Strategy — A 4-6 Week Study Plan

A focused, consistent plan is more effective than sporadic cramming.

Weeks 1-2: Foundation & Core Topics. Dedicate this phase to mastering the top three topics. Solve 15-20 problems on Arrays (focus on two-pointers, sliding window), 10-15 on Bit Manipulation, and 10-15 on Greedy algorithms. Use platforms like CodeJeet to filter problems by company and topic. Ensure you can implement patterns like the sliding window above from memory.

Weeks 3-4: Difficulty Progression & Pattern Integration. Shift to solving problems by difficulty. Aim to solve 30+ Easy problems until they feel trivial. Then, tackle 20-25 Medium problems, focusing on integrating patterns. For example, a Medium problem might combine an array traversal with a greedy choice. Finally, attempt 5-10 Hard problems weekly. Don't aim for perfection; focus on breaking them down and writing partial, logical code.

Weeks 5-6: Mock Interviews & Company-Specific Practice. Simulate the real interview. Use CodeJeet's AON question bank and do timed mock interviews (90-120 minutes for a set of 4 questions with the given difficulty distribution). Practice verbalizing your thought process aloud as you code. Revisit any previously solved problems that were challenging.

Key Tips

1. Communicate Relentlessly. Before writing a single line of code, state the problem in your own words, ask clarifying questions, and outline your approach. Explain the time and space complexity of your initial idea and any optimizations.
2. Prioritize Clean, Correct Code for Easy/Medium. For the first three questions, correctness and readability trump cleverness. Use clear variable names, add brief comments for complex logic, and handle edge cases (empty input, single element, large values).
3. For the Hard Problem, Show Process. If you hit a wall, don't freeze. Articulate a brute force solution, analyze its inefficiency, and then discuss potential optimizations (e.g., "This is O(n²). Perhaps we can use a hash map or sort the array to get to O(n log n)"). Writing a working, sub-optimal solution is often better than a silent, incomplete optimal one.
4. Master Your Language's Standard Library. Know key utilities by heart: sorting, data structures (heap, deque, ordered map), and common algorithms (binary search). Fumbling with syntax wastes precious time.

Consistent, topic-focused practice is the most reliable path to success. Understand the patterns, internalize the code, and practice under realistic conditions.

Browse all AON questions on CodeJeet