Day: December 2, 2025

• Shubham Malhotra is a software engineer at Amazon with experience at Microsoft and Salesforce.
• He has five proven strategies that he’s used to land all of his Big Tech software engineering jobs.
• He emphasizes the importance of internships, tailored résumés, and job search timing for career success.

Shubham Malhotra’s Big Tech journey began during his fifth semester at the Rochester Institute of Technology (RIT), where he was juggling coursework with a co-op at a real estate-focused tech firm.

While gaining experience and refining his résumé, Malhotra — who grew up in New Delhi, moved to the US to study software engineering, and is now a software engineer at Amazon — applied to roles at top tech companies.

He landed internships at Salesforce in the summer of 2021 and at Amazon AWS in the fall of 2021. During his second internship, he applied for a full-time position at Microsoft through a job portal and ultimately secured an offer for 2022.

Malhotra stayed at Microsoft for two and a half years before leaving the company in November 2024, when he relocated to the Seattle area to join Amazon.

Here are five job-search strategies he employed to secure multiple offers from Big Tech companies.

1. Take initiative during internships

Malhotra believes that completing purposeful internships on systems-focused teams was a significant factor in his success. “Breaking into Big Tech is hardest at the beginning,” he said. “For me, that breakthrough came via internships at Amazon and Salesforce, which gave me enough credibility to land my Microsoft offer.”

Treating his internships like “engineering labs,” Malhotra said he used these experiences to intentionally build up infrastructure, performance, and systems expertise far beyond surface-level coding.

“I wasn’t just doing ‘intern tasks’ — I was already solving latency and error-tolerance issues that directly affected customers and operational SLAs,” he said. “This was mostly driven by my own initiative, with support from my managers.”

During his internships at Salesforce and Amazon, Malhotra would ask his manager and senior engineers, “What’s a real reliability or latency problem on the critical path that no one has had time to fix yet?” From there, he’d volunteer to own a slice of it, then they’d scope it out together.

“Doing this complex problem-solving also helped give me great visibility within my teams,” he said.

These early experiences enabled him to craft a résumé that showcased both internships and technical depth, which he believes was key to landing his Microsoft interview. Then, the work he did to secure his internship offers meant he’d already practiced for the big leagues.

“Because I’d already been preparing through prior internship interviews, I was technically and behaviorally ready to interview for full-time positions at top tech companies.”

2. Write a résumé that works for both ATS and humans

Malhotra avoided generic buzzwords and focused on scale, reliability, and research contributions in his résumé. He also reverse-engineered company job descriptions to match his résumé with ATS filters.

“I used LaTeX via Overleaf to create a clean, technical résumé optimized for parsing and readability,” he said.

Another one of his strategies was tailoring keywords for each role, emphasizing “cloud computing,” “distributed systems,” and “backend engineering” throughout the document. Malhotra also ensured that his résumé bullets focused on measurable outcomes, rather than just effort.

“Every bullet emphasized not just tasks but quantifiable impact — like “reduced data latency by 40%” and “streamlined workflow to cut API response time by 25%.”

3. Time the market as a new grad

Malhotra wanted to ensure that he applied for Big Tech roles at the right time. “As a fresh graduate, I learned that timing your job search is just as critical as skills,” he said.

He began his application process early, around August, when most tech companies kick off full-time recruitment.

“From August to mid-November, companies fill the bulk of their head count for the next year,” Malhotra said. “After a brief halt, a second hiring window opens between February and April of the following year.”

Malhotra signed his Microsoft offer in October 2021. For his most recent move to Amazon as an experienced hire, his offer was also finalized in October with a November start date.

4. Scale interview prep to the role’s specific challenges

Malhotra prepped for coding interviews using LeetCode, CodeChef, and HackerRank, identifying weak areas and tracking performance.

For behavioral rounds, he followed the STAR method and mapped his stories to leadership principles. He also ramped up his preparation for interviews using white papers, books, and real-world architecture case studies to help him discuss company-specific challenges.

5. Don’t take shortcuts

Malhotra said he chose his college specifically for its co-op structure, helping him gain early real-world experience and build a strong US-based engineering track record.

Feeling confident in this background, he decided to try an out-of-the-box approach to his job search. Instead of relying on referrals, Malhotra cold-applied and followed up via LinkedIn with tailored pitches.

His cold outreach strategy centered on emailing recruiters with short, personalized pitches that included how he found their contact information, a brief introduction of himself, a clear ask to review his résumé for specific roles, and a note on why he was excited about the company.

His “short, personalized pitch” strategy played the biggest role in his Amazon transition.

“I leaned heavily on concise, personalized emails and LinkedIn messages to recruiters, plus a few warm intros,” Malhotra said. “Most of my serious interview loops, including the one that led to my current offer, started from that outreach rather than just submitting an application and hoping.”

He also developed personal projects, such as a handwriting recognition tool utilizing AWS Textract, which he hosted on the cloud with authentication and shared functionality.

“I treated job hunting like system design — mapping companies, targeting roles, cold emailing with personalized subject lines and value propositions,” Malhotra said. “I always kept a ready-to-send project repo or research paper link handy to prove my value.”

Malhotra is happy at Amazon

He’s working on deep-seated infrastructure problems that he believes have a real impact. “It’s exactly the kind of work I wanted when I first set my sights on Big Tech,” he said.

If he had to look for another job in today’s market, he says he’d use the same five strategies, but with one additional point.

“I’d run the same system again — just with a bit more compounding from public work and relationships,” Malhotra said. “I’d add an even stronger emphasis on building signal in public while things are going well — open-source contributions, writing, small talks, and a tighter network of engineers and hiring managers. Those make your résumé, outreach, and timing work even harder for you when the market tightens.”

• Lots of tech leaders like to say they hate ads.
• Then they decide that, actually, they don’t hate ads, because ads can help them make money.
• It seems like OpenAI and Sam Altman are headed that way with ChatGPT.

ChatGPT turned three years old the other day, which means we’ve spent three years in an AI frenzy.

It also means hundreds of millions of people have been using ChatGPT for years and … not seeing any ads at all, whether they’re using the paid version or the free one.

That’s not totally astonishing: We’ve gotten used to consumer internet products like Google, Facebook, and Instagram taking off without ads for a few years. And then, the deluge.

So how much longer will ChatGPT remain ad-free? And what happens when it isn’t?

Over the weekend, we got a hint that an ad push may be underway, via some code from ChatGPT’s Android app unearthed by developer Tibor Blaho:

Scouring apps for yet-to-be-released features is a long-standing tech hobby, and sometimes it really does yield results. It’s also entirely possible that what Blaho found is … something other than an ad product road map.

But it still seems very, very likely that ChatGPT will have ads at some point.

We know this in part because OpenAI executives, starting with Sam Altman, have suggested they will be coming (in 2024, Altman said ads were gross; this year, he allowed that maybe OpenAI could make “some cool ad product”).

We know it because OpenAI has been stocking itself with talent from Meta — one of the most successful advertising companies in the world.

And we know it because it’s simply logical: Altman says ChatGPT has around 800 million weekly users, and only a small percentage of them pay. At some point, his company will want to convert those non-paying users into revenue-generating ones, and ads are the obvious way to do that.

Meanwhile, The Information reports, OpenAI focus groups show that some ChatGPT users already assume ads play a role in the results they’re seeing. (I’ve asked OpenAI for comment; while we’re here, I’ll note that OpenAI has a business partnership with Axel Springer, which owns Business Insider.)

But all of that is different from saying ads are coming soon, or knowing what kind of ads OpenAI would want to put into ChatGPT. And it certainly doesn’t address the core question about what happens when you inject ads into an answer machine: Does that machine give you the best answers? Or the answers someone has paid to give you?

Which brings us to the next question: If ads do show up, what would they look like? Because sticking ads into an AI assistant isn’t like putting them next to search results or inside a news feed. There’s no feed. There’s just the answer.

There are a few obvious possibilities, none of which are mutually exclusive:

• Search-style intent ads

This is the Google model: You tell Google exactly what you’re looking for — “dumpling spot near me,” “best Chromebook” — and advertisers bid to appear next to those queries. If ChatGPT is now a legitimate Google rival, why not use Google’s business model, too?

• Personalized ads based on everything ChatGPT knows about you

This is the Meta model: Instead of bidding on queries, advertisers target people, based on what it has learned about their behavior, on and off Meta’s properties.

• Old-school text links

The simplest version: “You asked for the best toaster, here are three recommendations, one of which is sponsored.” That’s basically affiliate marketing. It’s low-key and probably the least lucrative.

• Multimedia ads

You are probably typing things into ChatGPT and reading its results. But it doesn’t have to work like that: ChatGPT can already talk and show you images. Via Sora, it can show you video. The magic device famed designer Jony Ive is building for the service likely won’t have any screen at all. All of which means that Altman and Co. may have a choice to serve you ads that aren’t tiny boxes of text on your phone.

But no matter what route OpenAI takes, all of its ad plans will have the same peril: the possibility that injecting paid messages in a service you count on could change your relationship with that service, and weaken that trust.

It’s a gnarly problem, even for a company that’s used to moving quickly and fixing messes after the fact. They might move more slowly on this one than some people think.