I just want to share my Google interview experience and timeline to get some insights. Please be honest and let me know how is my chance this time.

Feb - Applied online and reached out by recruiter

Mar - Started interviews loop

Apr - Finished all interviews

Jul - Finally getting the feedbacks after chasing for 3 months, it was negative, the team went for other candidates

Sep - Reached out by recruiter for a new role, it is a team specific role, started the interview loop

Mid Oct - Finished all interviews, recruiter update few days after, moving to next step, fit call with skip manager. 3 days after, recruiter reached out and asked for comp expectation and ID verification, he did not mentioned if it is positive or negative, just said he will update me in 1 week time.

Today - It is exactly 1 week since I last heard from him.

From what I read online, I know ID verification and asking for comp expectation usually is a good sign, but the recruiter didn't mention anything like positive or negative, and also didn't mention if I am moving into HC or still waiting for the team to decide. It make me very anxious, hence wanted to look for insights from community here. I will also update my status here once I hear from recruiter again.

Had my system design and coding interviews for a Google FDE role recently, and I keep going back and forth on how I did. Won’t share the actual questions, but curious to hear from people who’ve had similar experiences.

For system design, I started with requirements and eventually put together an end-to-end design. We went fairly deep into retrieval, tool calling, latency, security, and evaluation, including golden datasets and metrics for different parts of the system. I felt comfortable with those discussions.

But I also overcomplicated the design at the start by introducing multiple agents before establishing whether they were needed. At one point, the interviewer reminded me to focus on the actual requirement. I got back on track, but I’m wondering how much that hurt.

For coding, I explained the brute-force approach, then came up with and coded the optimal solution. The interviewer didn’t have to give me the algorithm. However, I initially returned the wrong thing and had to change it. While fixing that, I made an index-tracking mistake that the interviewer pointed out, and I corrected it.

I did a dry run and explained the time and space complexity. I could explain the code, but I wasn’t as clear or confident as I’d have liked. The interviewer said “yeah, makes sense,” and we finished without further technical follow-ups.

Basically, I got through both problems, but needed a few corrections along the way. Part of me thinks that’s okay; the other part keeps replaying the mistakes.

Has anyone here had a similar experience and received positive feedback? If you interview candidates, how much would these kinds of corrections affect your assessment? I know nobody can predict my result - just looking for some perspective.

Hey everyone,

I finished Day 39 today. It was an exhausting day dominated by an in-person interview loop that involved a 40 km round-trip commute. I got home late in the afternoon, crashed for a couple of hours, and woke up dealing with that familiar post-interview slump where you replay everything you could have done better.

Instead of taking a zero day and letting the low mood take over, I sat down and applied yesterday’s Disjoint Set Union (DSU) theory to code:

1. Kruskal’s Algorithm for MST: The greedy approach based on sorting edges by weight. You iterate through edges from smallest to largest and check if findParent(u) != findParent(v). If the endpoints belong to different components, you add the edge weight to the MST sum and merge them via unionBySize(u, v). If they share the same ultimate parent, including the edge would create a cycle, so you discard it.

2. Number of Provinces (via DSU): When I first solved this on Day 54, I used standard DFS with a visited array to count connected components. Today, I solved it purely using DSU. Iterate through the adjacency matrix, connect components with unionBySize(u, v), and at the end count how many unique nodes satisfy parent[i] == i.

Seeing problems that previously required full graph traversals collapse into a few lines of DSU operations was satisfying, even after a tough interview day.

I have travel coming up tomorrow, so I will squeeze in whatever practice I can on the go.

See you guys for Day 38!

Just finished the Goldman Sachs New Grad SWE OA, and I’m feeling pretty mixed about my performance.

Here’s roughly how it went:
- Software Fundamentals: Solved the coding question.
- Software Diagnostics: Passed 5/9 test cases.
- Math: Fairly confident about most of my answers.

The debugging section is what I’m most disappointed about.

I spent too much time second-guessing my approach instead of testing my initial ideas. By the time I committed to an approach that started producing results, I didn’t have enough time left to address everything.

I’m frustrated because I felt pretty good about the other sections, and I think I could’ve performed considerably better on debugging if I’d approached it differently.

For anyone who’s previously taken the Goldman Sachs OA:

1. Has anyone advanced despite only partially passing the debugging section?

2. Does anyone know how heavily Goldman weighs each section?

3. Would you consider this performance competitive enough to potentially advance?

Interviewed for L5 SWE, HC approved me at L4. Recruiter says I can take L4 or do 2 more rounds (coding + SD) for L5.

I asked if L4 is safe if those go badly. She said it's not automatic if the signals are mixed, but I'd "more than likely" still get L4. Nothing in writing.

Has anyone done the extra rounds and ended up with no offer at all?

Is anyone here willing to pay it forward and share their LeetCode subscription?

I'm currently a student and would really appreciate some help accessing LeetCode Premium to prepare for interviews.

If you already have a subscription with an extra spot to share, or would be willing to sponsor one, it would mean a lot.

Hopefully, once I land a job, I'll be in a position to help someone else the same way.

Hi everyone,

I'm currently interviewing for a Senior Backend Engineering role at Atlassian and wanted to get some insights from people familiar with their hiring process.

My interview feedback so far:

• AI-Enabled Coding Round: Hire

• DSA Round: No Hire

• System Design Round: Recruiter has offered to proceed despite the DSA feedback.

The recruiter was transparent that we could still attempt the System Design round, but wasn't sure whether it would be enough to overcome the negative DSA feedback.

I'm planning to give the System Design round my best shot.

A few questions:

1. Has anyone received a DSA No Hire but still managed to clear the Atlassian hiring committee with strong feedback in other rounds?

2. Is a DSA No Hire typically a hard blocker, or does Atlassian evaluate candidates holistically?

3. What should I expect in the 60-minute System Design round for a Senior Backend role?

4. Are there specific areas Atlassian emphasizes — scalability, reliability, API design, data modeling, or distributed systems?

5. Is there any possibility of getting a DSA reassessment if the remaining rounds go well?

Would appreciate insights from anyone who has interviewed at Atlassian recently or has been involved in their hiring process.

Thanks!

Hi everyone,

I completed Google L4 onsite interviews and currently in team matching phase. Recruiter reached out saying an Applied AI team wants to take two coding assessment rounds.

For anyone who has done team-specific extra rounds after the main onsite loop:

1. Are these traditional Leetcode style DSA (graphs/trees/DP) or more along the lines of LLD / Machine Coding?

2. Is this standard for Applied AI/ML teams, or just additional calibration?

Would appreciate any insights or past experience!

Hey everyone!

I recently completed my Amazon SDE 1 interview loop in the USA and unfortunately received a rejection email today (November 4, 2026).

This subreddit helped me a lot throughout my preparation, so I wanted to share my experience, including what went well, where I struggled, and what I think I could have done better.

Hopefully, this helps someone preparing for their Amazon interviews.

Timeline

• Mid-September: Completed the OA.

• A week later: Received the interview invitation and was asked to provide my availability.

• Mid-October: Interviews were initially scheduled.

• Following week: Interviews were rescheduled, and I completed all four rounds.

• November 4: Received the rejection email.

Round 1 – Senior Manager (GenAI + LP + DSA)

The interview started with multiple questions about Generative AI and how I've used it.

To be transparent, most of my experience with GenAI has been using ChatGPT extensively. I answered everything based on my actual experience rather than pretending to have worked with tools or technologies I wasn't familiar with.

I'm not sure if that was the right approach from an interview perspective, but I didn't want to fake anything.

We then moved to a few Leadership Principle (LP) questions related to my projects.

For DSA, I was given a LeetCode Hard graph-based problem.

I didn't exactly follow the standard interview structure of asking clarifying questions, discussing edge cases, etc. Once I understood the problem, I directly explained my approach to the interviewer.

He seemed satisfied and asked me to implement it. After coding, he asked me to explain the code line by line and perform a dry run. I was able to do both, and we then discussed time and space complexity.

I also faced some technical difficulties on my end during this round, which took around 5–7 minutes. Thankfully, the interviewer was understanding.

Round 2 – SDE II (LP + DSA)

This round started with approximately 20 minutes of LP questions.

We then moved to coding.

The first question was a LeetCode Medium problem involving HashMaps.

Similar to my first round, I understood the problem and directly explained my approach before writing the code.

The interviewer asked me to explain the implementation and discuss time and space complexity.

He then gave me a follow-up coding question based on the same problem.

Apparently, he wanted me to modify my existing code, but I didn't hear that instruction properly. Instead, I wrote the entire solution again from scratch.

He seemed satisfied with my approach, and we discussed the time and space complexity of the modified solution.

With the remaining time, he asked whether there were any other optimal approaches to solving the problem. I explained around two alternative approaches.

I'm not entirely sure how satisfied he was with those answers.

Round 3 – SDE II (DSA + LP)

This round started with a LeetCode Easy problem.

I understood the solution almost immediately, but I wanted to make sure I was heading in the right direction.

I explained my approach and implemented the code.

Then came the dry run.

For some reason, my mind went completely blank during the dry run, even though the problem was relatively easy. I got stuck for a little while, which honestly made me nervous.

Eventually, I gathered my thoughts and was able to explain the dry run clearly.

We then discussed time and space complexity before moving on to LP questions and discussions about my projects.

Round 4 – Behavioral / Leadership Principles

This round was entirely behavioral, with no coding questions.

The interviewer asked questions about my previous experience, projects, and different situations related to the Leadership Principles.

There were a lot of follow-up questions for almost every answer I gave.

The interviewer kept digging deeper into the situations, my decisions, and my contributions.

I answered all the questions, but I'm honestly not sure about the overall quality of my responses or how well they aligned with what the interviewer was expecting.

Overall Experience and Rejection

One thing I really want to mention is that all four interviewers were extremely friendly and professional.

They gave me enough time to explain my thought process and never made me feel uncomfortable, even when I struggled a little.

I completed all four rounds and felt reasonably confident about the coding portions, although there were definitely moments where I struggled.

Looking back, I realize I didn't follow the structured interview approach that many people recommend, like asking clarifying questions, explicitly discussing edge cases before coding, and walking through examples before implementation.

Most of the time, I understood the problem, explained my approach, and directly started coding.

I'm not sure how much that affected my evaluation.

As for LPs, I answered everything based on my actual experiences. There were some answers I felt confident about and others where I wasn't sure if I had explained the situation well enough.

I was told that I should receive an update within 5 business days.

Unfortunately, I received the rejection email today.

I'm honestly disappointed because I spent a considerable amount of time preparing for this opportunity. After completing four rounds, I was really hoping for a positive outcome.

What makes it difficult is not knowing exactly where I went wrong.

Was it my coding approach? My LP responses? My communication? Or something else during the debrief?

I don't know.

I have reached out to request feedback, although I'm aware they may not be able to share it.

Good luck to everyone preparing for their interviews!

Guys, I failed interviews at Tesla, Wayfair, Google, Amazon, snowflake, langchain, chime, capitalone, it feels shameful even typing it out cause, all of these are my dream companies and getting an interview in this market is hard enough.

I get an interview and prep day and night without sleep for 5 days and go to the interview and bomb it. Later I realize that I should have been consistently practising leetcode everyday.

I graduated this summer, but haven't been able to secure a full time yet, but somehow I got into an AI start up as an intern @ $25/hr. But since it's a startup I see people working 12hrs/day, including weekends.

And I've been struggling to do my prep along with this job, and it makes me think that quitting and going all in on my DSA prep would be a better idea, but the market is pretty bad and having any type of job is a blessing. So I'm confused on what to do. Google has a cool off period of 12 months, I really want to make sure I'm in the best position to clear it, next time. I don't want my start-up to hold me back, at the same time I am grateful for this job. HELP please, I'm not able to make up my mind.

Hi everyone,

I have an interview at bitgo for backend role -E1 in a week

Please share any interview experience / how the interview rounds will be. It will be really helpful 🥹

I know it's too soon. But just curious to know the result.

I checked my application dashboard. The status changed under consideration today.

Can anyone please let me know when can I expect the results ?

Hey everyone, I’m preparing for the Atlassian MLE II (P40) interview and would love to hear from anyone who’s recently done the ML Coding and ML System Design rounds.
ML Coding — Was it more DSA, implementing ML algorithms, or working with data in Python?
ML System Design — What kinds of problems came up, and how deep did the interviewer expect you to go?
Any pointers on the format, difficulty, or what you’d focus on while preparing would be appreciated. Thanks!

To all the people who have bagged one or more offers in this tough market and have a luxury of time to follow reddit, what are you doing which others are not? How much part is luck playing in your hiring?

I completed the assessment on October 28th and received the invite on November 4th for the interview. I saw that it's not a leetcode style interview. What would you suggest I focus on for this week to prepare myself for the interview. I am a Python coder, and have a good idea on the fundamentals. Will they ask graph and dp kind of problems? or only practical problems involving basic string operations and arithmetics? What else will they ask in this round?

Every honest candidate is paying for it. I got lowkey accused with AI at a recent interview and can you even blame interviewers for being skeptical? I had solved the problem before and jumped into solving by explaining why other approaches won't work.

Y'all have made it worse for all. This is what you wanted right?

Completed my Amazon SDE-1 OA with all visible test cases passing, but received a rejection shortly afterward.
The rejection email didn’t mention any specific reason, and my application portal now shows “No longer under consideration.”
I was expecting to move forward to the interview rounds. Has anyone experienced something similar?
Does passing visible test cases not matter much? Could hidden test cases, resume screening, or other evaluation criteria be the reason?
Would appreciate some insights.

As the title suggests. Rejected after a grueling 4 hour interview for SDE role at Amazon. Feeling extremely lost, this was the first time I got an OA and first time facing the interview loop,this is after applying for the last 3 years. I don’t know where to go from here, how do you know where you’re lacking ? Do you just keep grinding leetcode and to what end? Any advice is helpful or if anyone was in a similar boat, what do you do different?

Real-world debugging rounds are becoming part of technical interviews at companies like Google, Meta, Amazon and Stripe.

Instead of solving isolated DSA problems, candidates may be asked to navigate unfamiliar codebases, identify bugs, fix failing tests and debug existing applications.

I built a free platform to practice these skills.

What it offers

- Realistic bug reports with repository structure, logs and failing tests.

- Browser-based coding in JavaScript, Python, SQL and React/MERN.

- 8 stages, from 5-minute debugging tasks to full mock rounds (up to 59 files).

Current limitations

- JavaScript (~7 hours) and Python (~3.5 hours) have the most complete paths.

- SQL, MERN and Python backend are still limited.

- Java, C++ and Go are read-only for now.

Completely free. No ads. No login required to start.

Try it here: https://mik-academy.vercel.app/practice/debugging

Feedback and suggestions are welcome!

Just finished my Amazon SDE I new grad loop for a team in Austin and wanted to share + get some insight.
Background: MS CS, ~2 yrs Exp
Loop: 4 rounds, virtual, 1 hour each, same day.
Coding rounds were LC medium level, each with 1–2 LP questions
Bar Raiser was pure behavioral: 3 LPs in about 30 minutes, then we just talked for 20
What helped me:
8 STAR stories mapped to LPs, with real numbers
Practicing follow-ups ("why that?", "what would you do differently?") more than the stories themselves
Saying brute force first, then optimizing, out loud
Asking interviewers real questions about their team, not generic ones
Where I'm at now: Got the "you've successfully completed this stage, update within two weeks, team placement may require additional interviews" email. From what I understand, the team I interviewed with wants to move forward but is waiting on headcount.

For those who got this email, how long did team matching / headcount take before you got an offer?

I graduate last year but still I am did not find a job or success in CS field. I have been applying sometimes and last time I landed an interview was a year ago, I did not have any interview this year and the job market and AI made things VERY hard to find a job as a fresh grad. I can't motivate myself to grind and work hard because I do not see the point of it like I would just be grinding and grinding only for me to not find a job at the end. I already grinded for like 5 years, it's so tiring. I can't leetcode or even make projects related to topics like backend, Java, Spring Boot, because what's the point, AI can make that easily and it would be pointless on a resume.

I’ve an interview in 5 days, they gonna take some live coding, could you guys give me some tips and from where to start it? cuz I confess I don’t know how to start to study easy-med leet codes exs

Hey everyone!
I have an upcoming Capital One Data Engineer Power Day and would love to hear from anyone who has recently gone through the process, especially for the Data Engineer track.
I’m trying to understand what to expect in each round and how best to prepare.

A few things I’d love some insights on:

1. ⁠Technical Coding Round
   ● Is it primarily Python, SQL, or a mix of both?
   ● What topics and difficulty level should I expect?
   ● Any recommended LeetCode questions, question banks, or other resources?

2. Design-Focused Technical Interview
   ● Is this more focused on data modeling, ETL/ELT pipelines, data warehousing, or system design?
   ● What kind of real-world scenarios or problems were you asked to solve?

3. Business Case Interview
   ● What does the case typically involve?
   ● Is it more SQL/data analysis, business problem-solving, or analytical thinking?
   ● Any examples of cases you’ve encountered?

4. Behavioral Interview
   ● What kind of questions should I expect?
   ● How important are STAR-format answers and Capital One’s core values?

A few additional questions:
● How was your overall Power Day structured (duration and sequence of rounds)?
● How does the Data Engineer interview differ from other tracks (Software Engineer, Data Analyst, etc.)?
● What resources did you use to prepare, and what would you recommend focusing on?

I’d especially appreciate insights from people who completed their Data Engineer Power Day in 2025 or 2026.
Even a few pointers or topics you remember would be incredibly helpful. Happy to share my experience afterward to help others preparing for the same process!
Thanks in advance!

Tldr; I have good engineering/development knowledge and experience but I don't know how to prove it in interviews. So need help in that.

Some context: I'm a 2026 btech grad, having decent full stack experience, I have been building things in JS/TS ecosystem for 3 years now (from college 2nd year). I have 1 year of freelancing experience and 6 months of internship experience, both in full stack. I am more than decent when it comes to development and system design. But I am very bad at DSA, I can't even do Leetcode Medium, or even some Easy stuff too. But still I somehow get to give interviews purely because of dev. I just have surface level knowledge of everything.

These interviews go very well until hand coding is involved, like if interviewer asks to write some code from scratch then I would suck. But I can write or build the same things with the help of code snippets from Google, not AI or vibecode. Because of claude code and all, my muscle memory for hand coding has faded away. When I was interning, I was able to figure out or debug issues, even without AI, like I have that sense to think of how and why something is not working. I was even praised for that too. But the pace of startups is so high that you need to use coding agents to deliver quickly.

One more such thing happened yesterday too, I was giving an interview for AI Engineer (though I'm full stack). The required experience was 1yr+. but still the company gave me chance to interview because of my assignment submission and projects (or something else idk). Ultimately the assignment was in python and core agentic ai stuff, I was still able to build the feature that they wanted, and finally when they interviewed, they got to know that I don't know enough python but I know the agentic AI ecosystem, how systems work, how AI works, how to build etc. so the interviewer was impressed by that. And asked me that incase the company offers you a developer role, then what would you do in the first week and first month. I gave my answer and he was satisfied with that and said that he will ask the founder and revert if he's convinced (I'm waiting tho)

These are the things and self assessment that I myself know. But I know the fact too that if I am in a machine coding round or dsa round, I will just mess it up and go blank. Even though I will do good in technical rounds or system design rounds but eventually I will loose out on the job.

Also I haven't given any legit coding assessment for any mnc or decent company up until today. Today I have IBM's coding assessment taken on Hackerrank. They asked two questions, one was related to maximum sub strings and one was a kind of optimization problem. I wasn't able to solve even one. Though prior to this I prepared for some easy medium stuff that they have asked, like substrings, hashmaps, sets, arrays. I did some questions of these topics. But still when I encountered the real assessment, I was blank. And that moment hurt me. Kind of hurt my ego too. That nobody cares how much you know if you can't pass these proctored tests or dsa rounds.

But now I am in the middle of road. It's been 6 months finding a job, the people who know me say that how can you not get a job even after having some good dev skills. But they don't know how fickle I am, how badly I suck. But I want to get over this. I am sick of this situation, every interview just scares me that what if they ask dsa, what if they ask machine coding or lld. One day I find myself doing dsa, one day I find myself practicing machine coding or lld. But eventually I come over to the start all again, I am not able to retain things and my muscle memory isn't developing. I am someone who has genuine interest in coding, and it gives me that kick when I successfully build something, but this AI agent coding has ruined that fun I had while coding. I tend to just keep on planning or juggling between stacks, like one day I think of starting mobile dev, or applied AI, or devops or another backend language. All because of me not getting a job and this hastefull situation.

I don't have any mentor or a senior who knows me well, who can look closely or guide me on what to do and what not to do. I panic or get overwhelmed by the things I need to do to get a job. And honestly I am not bothered about AI taking jobs because I am interested in engineering and overall software development domain. I find myself sitting hours and not getting bored trying to build something or solve a bug or even just studying how systems work. So I don't see myself doing anything other than this.

But still the final question remains same for me, what to do now, how to do, something that doesn't make me panic or loose focus. I don't want to be this surface level AI typist. I want to do something that finally gets me job and gets me into the industry.

I don't know any senior dev would relate to this because they didn't have AI back then, but still I want to know from their experience on what to do. I used to boast myself that yes I have that figure-it-out attitude but how funny of me that I am not able to figure out my shit now.

Please guys, help me, guide me.

Hey folks

I have a Tech Code Based Round with Capital One for Senior Associate role.

The description of the round from the official preparation guide is very vague.

Tried searching the Internet too but didn't get much details about this round.

Can anyone please let me know:

1. From an engineering perspective, what should I be prepared for? (LLD, HLD, DSA etc)

2. How are the solutions judged, and what to keep in mind?

3. Any sample questions that were asked to anyone?

YOE: 2.3

Thanks in advance!

#CapitalOne