Avik Das

Here’s exactly how I would crack a $150K+ SWE job at Microsoft in 6 months. (A real strategy my client used to land interviews at Microsoft, Meta, and Stripe) Too many engineers prepare hard to crack MAANG. But they lack a solid strategy. Here’s the exact roadmap I'll follow if I wanted to land a SWE job at Microsoft. Step 1: Resume + Role Clarity → Reverse-engineer the JD Study at least 10+ Microsoft SWE job listings. Highlight recurring keywords, must-haves, and preferred tools. → Rewrite your resume like a product pitch Show measurable impact: Good: “Improved load time by 43%” Bad: “Worked on performance optimization.” → Make it keyword-optimized for ATS without sounding robotic. Step 2: Master DSA the Microsoft Way → Focus on patterns, not problems Microsoft LOVES: Sliding window Trees (esp. DFS/BFS) Graphs Dynamic programming → Suggested Platforms: Leetcode (Microsoft tag), Neetcode(dot)io roadmap, Grokking series on Educative → 2 problems/day + 1 mock interview/week = compounding prep Step 3: System Design (yes, even for junior roles) → Start with High-Level Design (HLD): Learn how to design APIs, caching, rate limiting, and DB scaling. → Build a project where you actually implement what you learn. Step 4: Microsoft-Specific Behavioral Prep → Microsoft uses structured behavioral interviews Focus on “3As” framework: Action → Approach → Aftermath → Use real projects to show: Collaboration Adaptability Customer focus Engineering rigor → Prep 8–10 STAR stories mapped to their values Step 5: Mock + Real-World Practice → Do 4–5 peer or mentor-led mock interviews (especially for behavioral + design) → Record yourself. Watch for filler words, unstructured answers, lack of metrics. → Apply for 5 roles/week—Microsoft + similar-sized companies (to get into interview flow) Step 6: Apply Strategically + Use Referrals → Connect with 3–5 engineers/recruiters/week on LinkedIn. Don’t ask for a referral right away - engage first. → Reach out using tailored messages like: “Hi [Name], I’ve been preparing for an SWE role at Microsoft. Your journey from [X] to [Microsoft] really stood out. If you're open, I’d love to learn more about your experience.” → Submit applications using referrals whenever possible + 1-click apply where relevant The client who followed this playbook now works at Microsoft Azure and had 3 competing offers before accepting. It’s not about doing everything. It’s about doing the right things in the right order. Give yourself 6 months and follow this roadmap to make it a reality. Share this with someone who dreams of working at Microsoft. P.S. Follow me if you are a tech job seeker in the U.S. I share practical advice that gets you hired. — Additional resources: https://lnkd.in/eKxQmYtP. https://lnkd.in/gwRWpXR9. https://lnkd.in/g94_Cziv

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Here’s exactly how I would crack a $150K+ SWE job at Microsoft in 6 months. (A real strategy my client used to land interviews at Microsoft, Meta, and Stripe) Too many engineers prepare hard to crack MAANG. But they lack a solid strategy. Here’s the exact roadmap I'll follow if I wanted to land a SWE job at Microsoft. Step 1: Resume + Role Clarity → Reverse-engineer the JD Study at least 10+ Microsoft SWE job listings. Highlight recurring keywords, must-haves, and preferred tools. → Rewrite your resume like a product pitch Show measurable impact: Good: “Improved load time by 43%” Bad: “Worked on performance optimization.” → Make it keyword-optimized for ATS without sounding robotic. Step 2: Master DSA the Microsoft Way → Focus on patterns, not problems Microsoft LOVES: Sliding window Trees (esp. DFS/BFS) Graphs Dynamic programming → Suggested Platforms: Leetcode (Microsoft tag), Neetcode(dot)io roadmap, Grokking series on Educative → 2 problems/day + 1 mock interview/week = compounding prep Step 3: System Design (yes, even for junior roles) → Start with High-Level Design (HLD): Learn how to design APIs, caching, rate limiting, and DB scaling. → Build a project where you actually implement what you learn. Step 4: Microsoft-Specific Behavioral Prep → Microsoft uses structured behavioral interviews Focus on “3As” framework: Action → Approach → Aftermath → Use real projects to show: Collaboration Adaptability Customer focus Engineering rigor → Prep 8–10 STAR stories mapped to their values Step 5: Mock + Real-World Practice → Do 4–5 peer or mentor-led mock interviews (especially for behavioral + design) → Record yourself. Watch for filler words, unstructured answers, lack of metrics. → Apply for 5 roles/week—Microsoft + similar-sized companies (to get into interview flow) Step 6: Apply Strategically + Use Referrals → Connect with 3–5 engineers/recruiters/week on LinkedIn. Don’t ask for a referral right away - engage first. → Reach out using tailored messages like: “Hi [Name], I’ve been preparing for an SWE role at Microsoft. Your journey from [X] to [Microsoft] really stood out. If you're open, I’d love to learn more about your experience.” → Submit applications using referrals whenever possible + 1-click apply where relevant The client who followed this playbook now works at Microsoft Azure and had 3 competing offers before accepting. It’s not about doing everything. It’s about doing the right things in the right order. Give yourself 6 months and follow this roadmap to make it a reality. Share this with someone who dreams of working at Microsoft. P.S. Follow me if you are a job seeker in the U.S. I share practical advice that gets you land $150k+ roles in top companies.

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You are in a system design interview at Amazon for an SDE-3 role and the interviewer has given you the question to Design Netflix. He then asks a follow up to you: How does Netflix knows when to show: Are you still watching? Is it just time-based? If it were time-based, you would see it every time. So what is actually going on under the hood? Both look like a simple pop-up. Underneath, it is a mix of product thinking, client logic, and backend events. Btw, if you’re preparing for system design/coding interviews, check out our mock interview tool. You can use it for free here: https://lnkd.in/gpCn7t2T [1] Start from the product goals The feature is not only about nagging people. - Save bandwidth and CDN cost if the viewer has slept or walked away - Avoid autoplaying potentially sensitive content in an empty room - Protect kids if parents start a show and leave the TV on - Do all this without annoying active binge watchers So the design must answer one question: "When is the user probably not here any more" [2] Naive design - pure timer Simplest idea: - If playback has been running for 2 hours, show Are you still watching - If user clicks "Yes", reset the timer Why this is weak: - Someone can binge 5 episodes in a row and gets interrupted in the middle of an intense scene - Someone can start a show, walk away after 5 minutes, and the platform will keep streaming for the next 2 hours - It ignores how many episodes were auto played, device type, time of day, user habits  [3] Realistic design - session and engagement signals Think in terms of a "watch session" and "engagement events". Signals the client can track: - Play, pause, seek, volume change - Episode finished and next episode auto started - Remote or keyboard input, UI navigation - Screen on or off events from the device - For mobiles: app background or locked state A common heuristic could be: - Count how many episodes have auto played without any user interaction - Track how long it has been since the last button press or navigation - Only trigger the prompt when both are high enough Example rule: - If 3 episodes in a row have auto played - And there has been no interaction for 45 minutes - Then, before starting episode 4, show Are you still watching This feels much smarter: - Active viewers who pause, skip intro, change volume keep resetting the "engagement clock" - Sleeping viewers do not touch anything, so the next episode is blocked by the prompt  [4] Client heavy vs server heavy design You can talk about two design choices. Client first: - All logic runs inside the app on TV, mobile, or web - Client keeps an in memory session model and decides when to show the popup - It still sends telemetry events to backend for analytics and future tuning Pros: - Works even with flaky network - Highly responsive, no extra server round trip Cons: - Logic must be implemented and updated across many platforms - Harder to quickly roll out rule changes Continued ↓

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Hiring one mid-level engineer in the U.S. under H-1B rules can cost ~$307,000 in the first year. In Pakistan, a comparable remote engineer costs $20,000–$35,000 per year. That’s a 10–15× saving. For the cost of one H-1B engineer in the U.S., a company could instead outsource an entire remote team in Pakistan including 1 Product Manager 3 Software Engineers 1 QA Tester 1 UI/UX Designer and still spend less than half of the U.S. cost. This allows startups and enterprises alike to deliver full projects offshore at a fraction of the budget. If even 5–10% of U.S. H-1B demand shifts offshore, Pakistan’s IT export revenues (currently ~$3.5–4B annually) could increase by $1–2B in 3 years. The disruption to Indian IT firms opens the door for Pakistan to capture more contracts, especially in software development, fintech, and product outsourcing. Pakistan’s cost advantage makes it attractive for outsourcing, but long-term success depends on more than low prices. To become a true strategic partner, the workforce must strengthen soft skills, business understanding, and professional setups like reliable internet, modern offices, and time-zone alignment.

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$100K H-1B visa fee: A challenge or an opportunity for India? With the recent order imposing a $100,000 fee on H-1B visas, many predict tough times for Indian tech talent in the US. But here’s another way to see it — this could accelerate a shift we were already witnessing: global companies investing more in India. We already have a strong talent pipeline and competitive salaries. The next step is clear — we need to create the right environment and culture to innovate. That means: - Expanding beyond metros into Tier-2 cities. - Building ecosystems where engineers don’t just deliver, but invent. - Solving infrastructure and workplace challenges that hold back creativity. - Taking the best from Western corporate culture (clarity, meritocracy, ownership) and blending it with India’s sense of belonging, community, and “individual first → team first” mindset. This is not just about support work moving here. It’s about India stepping into a leadership role in global innovation. I truly believe — this century belongs to India. 💡 What do you think — is this policy a setback, or a catalyst for India to lead? 🔗 Source: https://lnkd.in/d6DFUQut #H1B #TechInIndia #Innovation #Bharat

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India could lose $140 billion annually if Trump’s proposed H-1B visa fee goes through. A suggested $100,000 fee on H-1B visas would effectively dismantle the program, which has been a lifeline for hundreds of thousands of high-skilled professionals—especially from India. 1. India is the world’s largest recipient of US remittances, receiving about $140 billion annually. These inflows make up nearly 30% of India’s tax revenues, supporting economic growth and currency stability. 2. About 71% of all H-1B visa holders are Indians. In 2025, ~399,395 H-1B visas were approved, of which nearly 285,000 went to Indians—primarily in the tech sector. This means nearly 300,000 Indian professionals in the US could be directly impacted. 💡 The consequences? A massive hit not just to Indian families and the Indian economy, but also to US companies that rely on top global tech talent to stay competitive. More Indian professionals may start shifting their focus toward Gulf countries like the UAE and Saudi Arabia, where tech ecosystems are rapidly expanding and policies are becoming more talent-friendly. #H1B #USIndia #TechTalent #Immigration #Economy #FutureOfWork #UAE #SaudiArabia

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System Design interviews don’t reward memorization. They reward clarity. Because today, system design is no longer “for seniors only.” Even SDE1/SDE2 interviews test whether you can think at scale - users, latency, failures, cost, and reliability. That’s exactly what this guide covers. It breaks down 10 must-know system design architectures that show up again and again in interviews - along with the core components, scaling tricks, and the exact “interview gold points” for each system. Instead of random theory, it trains you to explain systems like an engineer. How requests flow, where bottlenecks happen, what components matter most, and what tradeoffs interviewers actually care about. The 10 Designs Covered Inside : 1. It starts with fundamentals like a URL Shortener - then expands into real-world architectures like: 2. A Messaging System (WhatsApp) that handles delivery, retries, ordering, read receipts, and offline users. 3. An Instagram Feed that teaches fanout-on-write vs fanout-on-read and ranking tradeoffs. 4. A Video Streaming system (YouTube/Netflix) that shows the encoding pipeline, chunking, and why CDNs dominate scale. 5. A Ride Sharing system (Uber) built on real-time GPS streams, ETA accuracy, and geospatial indexing. 6. A Web Crawler (Google) designed as a pipeline: discover → fetch → parse → index with deduplication. 7. An E-commerce system (Amazon) showing inventory consistency, idempotent orders, and event-driven flows. 8. A Food Delivery system powered by workflow engines and state machines for reliable tracking. 9. A Spotify architecture where streaming + personalization becomes the retention engine. 10. And a Dropbox file sharing system where metadata + versioning is the real product. If you can explain these 10 clearly, you’re already ahead of most candidates - because these designs cover almost every interview pattern: caching, queues, sharding, consistency, fanout, CDN, state machines, and observability.

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It was 8:42 PM at the Amazon office when Priya, a senior engineer, noticed a Slack message from Raj, the newest backend SDE on her team. “Hi Priya, the orders API endpoint you own is suddenly returning 503s after my changes. Could you help me debug? Sorry for the late message.” Priya hesitated for a second. She’d spent months refining that endpoint, handling edge cases, scaling for Prime Day traffic, even documenting the entire flow for new team members. She remembered her own early days, when breaking something felt terrifying, and the seniors weren’t always patient. For a split second, Priya wanted to reply, “It was working fine earlier. Did you check the wiki?” But she didn’t. She joined the call. Raj was clearly stressed, walking through his recent commits. First month at Amazon, production issue, and it was late. Priya listened, asked focused questions, and together they tracked down a missing API key in the environment config. Raj sighed, “Thank you, Priya. Didn’t mean to break anything, just trying to add new promo logic.” Priya replied, “No worries. Bugs happen to all of us. What matters is catching them fast. I’d always rather have a teammate who asks for help than one who hides a problem.” The next morning, Priya shared a quick note in the team channel: > “Thanks to Raj for surfacing the issue quickly and collaborating on the fix. These things happen, what counts is how we respond.” And as she updated her notes, Priya reflected: → Being smart is good but being reliable, calm, and collaborative under pressure is what builds trust. → The most critical projects rarely go to the “lone genius.” They go to the person the team can depend on, day after day. Over time, more teammates started coming to Priya for tricky launches, because she was steady, approachable, and always showed up when it mattered. Because in the long run, that’s what makes you the engineer everyone trusts to deliver. And that’s the reputation that really opens doors.

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One thing your manager will never tell you Your promotion depends less on your performance and more on whether your team is actually growing. When I joined Amazon as an SDE-1, my team had 25 people. By the time I became Senior, it had 120+. Looking back, my “fast promotion” wasn’t magic. The org was expanding like crazy and growth creates opportunity. Here is the part people don’t like hearing: ❌ If your team hasn’t grown in years, your career won’t either. ❌ It doesn’t matter how good you are. There is nowhere to go. ❌ The only real path up becomes waiting for someone above you to leave. So if you want to grow faster: Choose teams that are growing. Not teams that are comfortable. Skills matter. Environment matters more.

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US H-1B visa rule may change : From a random lottery to a wage-based selection system. Here is how it will impact software developers : Fiscal Year 2026 wage levels (Silicon Valley Area): • Level I (Entry): $135,700 /yr • Level II (Qualified): $161,637 /yr • Level III (Experienced): $187,575 /yr • Level IV (Fully Competent): $213,512 /yr Rule is simple : Sort the application based on Salary, Give visa from top to bottom. Under the proposed H-1B rule, applications would be selected by wage level, highest first. That puts Level III–IV roles (mid-career to senior) at a clear advantage and Level I roles at a disadvantage. This is a structural shift : from lottery luck → salary power. Open questions: 1. Does “wage” mean base salary only or total compensation (cash + RSUs/bonuses)? 2. How will startups, research labs, and small businesses compete with Big Tech salaries?

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🚨 60 day grace period for H1B workers who lost their job is no more Most software engineers moving to the US for a job do so with a H1B visa – you can get a L1 (but then your stay is tied to the company) or an O1 (but that's fairly restrictive). In the past, in case you lose your job, you could stay 60 days in the country to find another job. After that, you have to leave the country but can still come back if you get a new job and get your H1B transferred (e.g. you don't need to go through a lottery again) The issue now seems to be that the 60 days grace period is gone[1], so essentially you have to immediately leave the country once you're laid off. Being an immigrant always come with some uncertainty on your situation but this wasn't too much a problem in the past because: - Tech companies were not doing laid off - The job market was in favor of engineers – it was easy to just find another job - While 60 days is kind of short, it was still enough in many cases (or at least to sort part of your personal situation) This is a pretty big blow for the industry – while some (especially younger folks?) will still move to the US, less and less will be willing to do (especially if you have no short path to a green card) The situation is also even worst for people in the current situation that may be overstaying because their 60 days grace period was suddenly gone and may not be able to transfer their H1B visa after 🙁

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I woke up today to some surprising news - Trump has just announced a $100,000 annual fee for every H-1B visa. For context, H-1B is the visa most Indian engineers (and many others worldwide) use to work in the U.S. Until now, companies were paying just a few thousand dollars per visa. This sudden jump is massive. Tech giants like Google, Microsoft, and Amazon rely heavily on H-1B talent. And for Indian IT firms like Infosys, Wipro, and TCS - this could be a real shake-up. Their U.S. strategies are already being questioned, and even stock prices have started reacting. But beyond the business side, I can’t help but think of the individuals. Thousands of professionals and students aspire to the U.S. dream through this route. For them, this move creates a lot of uncertainty and anxiety. What might change? 👉Companies may reduce H-1B visa based hiring. 👉 Offshore/remote work could rise. 👉 U.S. firms might focus more on local talent. Legal battles are almost certain, since many are questioning if such a fee is even enforceable. This is still developing, but one thing’s clear: global tech hiring strategies won’t look the same after this. #H1B #Tech #Immigration #FutureOfWork

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I am a Software Engineer at Meta with almost 2 decades of experience. Here’re the 5 learnings if you want to grow faster as a SWE: 1. Know the next level before promotion After you are performing well at your current role expectations, start approaching the next level. - Learn from seniors, understand their perspective - Look for areas you can help & can get noticed In short, prove that you deserve the promotion before you ask for it. 2. Become your own user - go on reddit or twitter threads - read through the users feedbacks and conversations - be empathetic & maybe have a conversation with few users This shift helped me move beyond just shipping features to actually improving the experience. 3. Data is your saviour Start diving into logs, events, and exceptions more deeply. - Where are users spending the most time?  - What’s making them drop off? - What are the most common exceptions?  - Which workflows are unintuitive? You can make better engineering decisions if you spend some time consuming the data 4. Every problem is not yours to solve Ask yourself: - Is this issue truly high-impact, or am I just trying to get it off my plate? - Is this a problem I should solve, or is it better to guide someone else to take it on? - Delegating was tough at first. But it’s crucial to identify your problems and delegate rest. The best engineers I’ve worked with aren’t the ones who take on the most work—they’re the ones who ensure the right work gets done by the right people. 5. Be a force multiplier - document more to save others time - build tools and scripts that automate tedious tasks - Guide others to help achieve their goals   Your team will move faster, and you will become more valuable—not just as an engineer but as a force multiplier. => Final Thought: The biggest shifts in my career didn’t come from just writing better code—they came from these small shifts. If you’re looking to grow as an engineer, try incorporating some of these steps into your own journey. Raman Walia

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