Shubham Sharma
@shubham1_sharma
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Software Engineer | Daily tweets on tech trends | LinkedIn: 170k+ followers | Letβs collaborate π€
Noida, Uttar Pradesh
Joined October 2019
Everyone wants a high-paying SDE job in 2026β¦ but very few know the real roadmap. Hereβs the EXACT playbook (with numbers) to hit $120Kβ$250K offers. π§΅
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7οΈβ£ The 2026 Backend Formula (Read Twice) π Modern backend stack π Scalable projects π System design π 100 smart DSA questions π Metric-driven resume π Public proof of work Follow this and $120Kβ$250K isnβt a dream, itβs expected.
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6οΈβ£ Build Public Proof of Work Backend devs who show real results win faster. π Share API benchmarks π Post architecture diagrams π Show before/after performance graphs This attracts inbound recruiters (the ultimate flex).
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5οΈβ£ Your Resume Should Hit Like a Performance Report Backend hiring managers LOVE metrics. π βReduced latency by 35%β π βHandled 50K req/minβ π βImproved throughput by 22%β Metrics = instant trust. Trust = interviews.
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4οΈβ£ DSA for Backend (The Only 100 Questions You Need) Stop grinding 500+ problems. π 30 Arrays/Strings π 20 Hashing π 20 Trees/Graphs π 15 Heaps π 15 Misc This covers 90% of patterns companies ask.
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3οΈβ£ System Design = Your Biggest Cheat Code 2026 interviews are system-design heavy, even for juniors. Learn: π Caching π Database sharding π Load balancing π Rate limiting π Queues This single skill boosts your offer size more than DSA ever will.
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2οΈβ£ Build Projects That SCREAM βI Can Scaleβ Forget to-do apps. Build things that look like production. π API that handles 1M+ requests π Microservice architecture with auth + payments π Queue worker using Kafka/RabbitMQ These projects get 5β7x more interview calls.
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1οΈβ£ Master the βMoney Stackβ of 2026 Companies arenβt hiring generalists anymore, they want specialists. π Go / Java / Node π Postgres + Redis π Docker + Kubernetes π AWS (EC2, S3, Lambda, RDS) This stack puts you ahead of 75% of backend devs instantly.
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π₯ Backend developers are about to become the highest-paid engineers in 2026. If you want $120Kβ$250K roles, read this carefully. Bookmark it.
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8οΈβ£ The Final Formula (2026 Reality) β
Strong fundamentals β
Real projects β
Modern stack β
DSA + System Design β
Clean resume β
Online proof of work π Combine these and $120K+ roles become realistic even for freshers.
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.@USPS redacted 500+ pages of internal records. Whoβs really seeing your info? AFFT is finding out. Watch here:
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7οΈβ£ Negotiate. Always. Most SDEs leave $15Kβ$40K on the table because they donβt negotiate. Companies expect it.
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6οΈβ£ Apply the β30β10β3 Ruleβ Weekly π 30 targeted applications π 10 recruiter reachouts π 3 referrals This method alone has a 25β40% interview conversion rate.
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5οΈβ£ Build Proof of Work on the Internet π GitHub green graph π 1β2 technical threads π Mini open-source contributions This attracts inbound opportunities without applying.
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4οΈβ£ Your Resume Should Pass ATS in 6 Seconds Use: β
Metrics (10K users, 20% speed boost) β
Action verbs β
Direct tech stack A single metric increases callbacks by 35%.
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3οΈβ£ DSA, But Smarter (not 500 questions) Do 120 high-impact problems: π 40 Arrays/Strings π 30 Trees/Graphs π 20 DP π 30 Misc (Stacks/Queues/Heaps) This covers 90% of interview patterns.
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2οΈβ£ Build 3 Portfolio Projects That LOOK Like Work Experience (Not calculators & to-do apps.) Examples: π A scalable API with 1M+ dummy requests π Realtime chat app with WebSockets π A full microservice system These projects get 5x more recruiter responses than normal ones.
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1οΈβ£ Learn the β2026 Tech Stackβ (Not the old one) π Backend β Go / Java / Node π Frontend β React + TypeScript π Cloud β AWS (80%+ companies) π Databases β Postgres + Redis Mastering this combo alone puts you above 70% of candidates.
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Higgsfield Recast's SOTA character swap is what Wan 2.2 Animate users thought they were getting.
Video character swap PERFECTED. Introducing Higgsfield Recast. 1-click full-body replacement with flawless gesture tracking + voice cloning + multi-language dubbing & background transformation. Scale your content income 10x overnight. 9 hr: follow & rt & reply for 211 credits
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Using memory with LLMs reduces token usage 60-80% (depending on the memory solution you choose), while improving context and accuracy. If you use Memori OSS, you will have 80% savings, token usage and total costs drop to 20% of the original: $11.25 β $2.25 per 1 M tokens
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This Resume template that worked for me ! ππ Comment "Resume", I'll DM you the template link.
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The fastest product teams donβt code faster - they learn faster. The edge isnβt technical anymore, itβs cognitive. @Zerve_AI gives your team instant visibility into whatβs working, Itβs not a tool; itβs insight on tap: https://t.co/2WEwMcxHXi
#ProductOps #InsightDriven
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