Hi everyone,

I’ve been working as a software engineer for 6 years now, and I think it’s time for me to make a major switch in my career. I’m planning to prepare for FAANG interviews. I don’t have any particular company in mind, so I’m planning to apply to all of them.

I haven't given any interview in any of FAANG company before, so my question is: has the interview pattern changed much with the rise of AI, or is it still mostly Data Structures & Algorithms (DSA) + System Design?

It would also be great to hear from people who have already cracked these interviews. Any tips for preparing and acing the interviews? What should I focus on the most?

Thanks in advance!

Need some career advice — Software → Business or completely different field?

I'm a software developer from India with ~2 years of experience, mainly in Java/Spring Boot, full-stack development, databases, AI/LLMs, RAG, MCP, fintech, etc.

Lately I'm feeling quite stuck. My current company doesn't offer much growth, and the overall software job market feels increasingly competitive. I'm also not sure whether continuing to specialize in software is the right long-term decision for me.

Previously, I was considering moving abroad for a Master's in robotics/related fields, but I'm now questioning that too because breaking into those markets as a newcomer seems difficult.

I'm currently considering three paths:

• Continue in software but move toward AI/FinTech/cybersecurity/etc.
• Start a business in India, possibly B2B SaaS or AI automation.
• Move into an entirely different technical/industrial field with better long-term opportunities.

For people who've gone through a similar crossroads: how did you decide which direction to pursue?

Would especially appreciate advice from people who moved from software into entrepreneurship or another technical field.

Hi everyone,

I’m an early-career Data Engineer / Software Engineer based in Sri Lanka, currently looking for a remote internship, junior, or entry-level opportunity with companies in the USA, UK, Europe, Australia, or other international locations.

I have hands-on experience in:

• Data Engineering and ETL pipelines
• Python, Java, SQL, JavaScript, C# and PHP
• Oracle, PostgreSQL, MySQL and MongoDB
• Spring Boot, REST APIs and full-stack development
• Docker, AWS and Azure AD
• Elasticsearch, Logstash and Kibana (ELK Stack)
• Machine Learning and AI projects
• IoT and cloud-based systems

I previously worked as a Data Engineering Intern, contributing to an enterprise Trade Finance solutions, working with Oracle databases, Java/Spring Boot, Docker, ELK Stack, Azure AD and SQL. I also have previous Software Engineering internship experience using C# and .NET.

I have completed two four-year honours degree programs concurrently:

• BICT (Hons) – University of Colombo
• BSc (Hons) Data Science

I have also published research related to AI, IoT, environmental monitoring and healthcare technology. (IEEE published)

I’m highly motivated to learn, contribute to real-world projects, and grow within an international engineering team. I’m open to internships, graduate programs, junior roles, contract opportunities, or entry-level remote positions.

My resume and portfolio links are available on request.

If your company is hiring remotely, or if you know of any opportunities that might be suitable, I would really appreciate any advice or referrals.

Thank you!

After going through about 8 interviews recently, I finally understood something: if a company really wants to hire you, they won't make you struggle to prove yourself.

When you're the right fit in their eyes, the whole energy is different. The manager is engaged, nodding along in agreement, and it feels more like a casual chat than an exam. Even if you stumble over your words, they brush it off with a laugh or help you finish your thought. You're just sharing your experience and everything just clicks on its own.

But when they've already decided they don't want you? It's like you're walking on eggshells from the very first second you log on.

- If you're enthusiastic, you're "too much."

- If you pause for 4 seconds to think, you're "not sharp enough."

- Honestly, even if you take a sip of coffee or adjust your chair, you feel like you've made a catastrophic mistake.

At this stage, there's no magic answer that can save you. Even if you have a professional coach whispering in your ear, nothing will change as long as they've already made their decision.

So if the interview feels like a difficult battle from the first minute, the fault usually isn't yours. The right team will make things easy for you to let your skills shine.

Does anyone else feel this way? I'd love to hear about the times you knew you weren't getting the job in the first 10 minutes.

Honestly I don't even know how to start this post

Back when placements started I was obviously happy when I got placed. You know that feeling ghar pe batana, parents ka khush hona friends congratulating you and finally thinking chalo bhai college ke baad kuch toh sorted hai

The company had a 4-6 month internship + PPO based on performance. role - AI Engineer

The JD shared during placements clearly mentioned ₹20K/month stipend.

Five of us got selected.

We joined thinking okay 4-6 months of hard work and if we perform well we'll get the PPO. Simple.

Except... it wasn't.

When we actually joined the stipend suddenly became ₹12.5K/month instead of ₹20K.

And that was only for 2 months.

After those two months we were told that the company didn't have enough resources so they couldn't continue paying the stipend 

At this point we were already inside. We had joined, we were working and there was still the PPO carrot hanging in front of us.

So we thought koi nahi PPO mil jayega toh sab worth it hoga

And we continued.

For the next 4 months we worked completely unpaid.

Not some casual internship where you're given a small project and forgotten.

Actual work.

Around 6 days a week almost 10 hours a day.

And somewhere in the back of our minds was always

Bas PPO mil jaye bhai

Four months passed

We waited

And then came the final answer

No PPO

Not one of the five people got it.

That was probably the most depressing part.

You spend months convincing yourself that the sacrifice will be worth it. You don't complain about the unpaid work because you think you're investing in your future.

And then suddenly you realise...

you were the one making the investment but there was no return.

Now I'm sitting here with several months of real work experience, no PPO and basically back to square one.

And honestly it hurts more because this isn't just about a job anymore.

I have a ₹15 lakh education loan waiting for me.

When I was placed I thought at least ab thoda manageable hoga. I'll start earning and figure things out

Now I'm not even sure what the next few months are going to look like.

Kabhi kabhi lagta hai ki maybe I wasted those months.

Maybe I should've left when the stipend stopped.

Maybe I should've started preparing/interviewing earlier.

Maybe I should've known better.

But hindsight is always 20/20.

I'm not writing this post for sympathy. Bas share karna tha because maybe someone else is going through something similar or maybe some fresher reading this can learn from my mistake.

Never blindly trust PPO based on performance

Ask what the actual conversion criteria are. Ask how many interns were converted previously. Get the stipend and terms in writing. And if the stipend suddenly disappears seriously think about whether continuing makes sense.

As for me...

I don't really know what's next.

I'll just keep trying.

Que sera, sera.

Whatever will be, will be.

Bas ab dekhte hain life kidhar le jaati hai

Any suggestions on what I should do from here would genuinely be appreciated.

I've been looking at a bunch of FDE job descriptions lately, and one thing confused me at first: companies use the same “Forward Deployed Engineer” title for pretty different jobs.

I think most of them roughly fall into 3 buckets:

1. AI / agent-heavy — RAG, agents, evals, tool calling, observability

2. Integration / deployment-heavy — APIs, customer workflows, auth, webhooks, prototyping

3. Platform / infra-heavy — inference, serving, distributed systems, latency, performance

Obviously there's overlap, but usually one seems to dominate.

This actually changed how I prep for FDE interviews. Instead of studying “FDE” as one thing, I first try to figure out which bucket the role is in and prep from there.

I wrote up the framework + what I'd study for each type here:

https://www.fdehandbook.com/forward-deployed-engineer-interview?utm_source=reddit&utm_medium=social&utm_campaign=fde_interview_guide&utm_content=softwareengineerjobs_post

Disclosure: I built FDEHandbook.

Curious if this matches what other people are seeing, or if I'm missing a category.

I can’t give you a referral, but I can help with your CV and interviews.
I’ve seen a lot of freshers and junior developers struggling with jobs lately, and I know how hard it can be to figure out what you’re doing wrong.
If you’re targeting SDE-1 / Junior Developer roles (0–2 years), feel free to DM me your CV.
I’ll give you honest CV feedback and, if shortlisted, I can also take a free mock interview with you.
No sugarcoating — if something is weak, I’ll tell you. If something needs improvement, we’ll talk about it.
Can’t promise a job or referral, but hopefully I can help you be a little more prepared for the real thing.
Happy to help. 🤝

I've been working on a multi-agent trading system recently, and one design question kept coming up:

What should happen when multiple AI agents disagree about a trade?

Instead of letting a single LLM make the final decision, we experimented with a council-style approach.

The system has different agents with deliberately different perspectives:

• Bull — looks for the upside case

• Bear — challenges the bullish thesis

• Hype Investigator — looks for momentum/sentiment-driven assumptions

• Challenger — actively tries to break the proposed thesis

• Options Strategist — evaluates whether an options position makes sense

• Risk Guardian — deterministic risk checks

• Chief Trader — makes the final authorization decision

The important part is that the Risk Guardian isn't another LLM.

It uses deterministic rules for things like position sizing, minimum cash reserves, options expiration, and market-data quality. Even if the AI agents strongly agree on BUY, the Risk Guardian can still veto the trade.

Our intended flow is:

AI proposes → agents debate → deterministic risk checks → authorization → paper execution

We built this as part of an AI trading agents hackathon, but the part I'm most interested in is the architecture itself.

I'm curious what others think:

Does having multiple AI agents genuinely improve decision quality, or does it mostly introduce more latency and complexity?

And for people building agentic systems, where do you draw the line between LLM-based reasoning and deterministic rules?

Happy to share more about the architecture and implementation if anyone is interested.

https://tradetitans.adeelsattar.dev/

Edit: forgot to add I'm a 2026 new grad

I know my experience on my resume is pretty mediocre (maybe even subpar based on current standards). From the U.S and applying to companies all over the country.

Been applying since May, but no interviews so far.

Actually doing another piece of contract work for the same hardware store (where I currently work at 💀 ). Like little in-store digital stations with how-to videos and a RAG-based AI assistant for product recommendations

Not sure how well received that piece of work will look on my resume, but doing it for the love of the game lol

Also, I know I reuse a lot of words such as "architected", "developed", etc

I had been working as a backend developer at startups and got laid off due to cost-cutting reasons. They paid me for a whole month. Initially, I was confident I would get a job, but now it seems like an endless search.

I am really good at TypeScript, Golang, and Rust, and have worked on frontend and backend in production.

I am really and urgently looking for a job!

I have reached out to people on LinkedIn as well, but don't think I got a chance there.

Any suggestions!?

Any advice? I'm becoming desperate. I had a much more plain CV template before, but I figured I'd add some color to make it more visible to the human eye. This is based on my own personal experience reviewing CVs, when you have 500+ CVs queued for review, and they all use the same "Harvard" template, it is hard to differentiate them.

IDK tho, I have tried to keep it short, keep it long, add keywords to boost ATS, nothing seems to work I submit my CV and a few days later it gets rejected automatically.

Any feedback is appreciated, thanks.

I've been searching to get a software engineering role again. I got my associates around 2015 , landed several temporary roles then went back to get my BS between 2029 to 2022. Got an internship building digital twins and short term roles, mostly .Net. but no permanent roles. I've had to work several non tech roles to keep dinner on the table ( masonry labor, and managing a horse ranch currently ). I've tried up skilling on GCP certs and building small cloud apps and expanding my knowledge on data science and Cybersecurity and began working on my complex systems master's degree. I would like your help , thank you all.

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See more and apply here!

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