Nandita Giri, a 32-year-old senior software engineer at Microsoft, shares her journey from Amazon to Meta to Microsoft, emphasizing how AI skills have become critical for career advancement in Big Tech. Giri, who studied at the National Institute of Technology in Kurukshetra, India, was hired by Amazon straight out of college in 2018 and moved to Seattle.
Her career trajectory demonstrates the growing demand for AI expertise in software engineering. At Amazon, she identified automation opportunities and successfully integrated AI-based solutions into team workflows, focusing on internal automation and data-driven decision support systems. After four years, Meta recruited her via LinkedIn in 2022, offering deeper opportunities in applied AI with large-scale data and infrastructure.
In 2023, Giri moved to Microsoft through an internal referral, attracted by the opportunity to work on enterprise-focused AI products like Copilot. She notes that with each role change, her scope of responsibility, impact, and compensation increased significantly.
Most importantly, Giri is largely self-taught in AI, spending hours outside work watching YouTube tutorials, reading blogs, and practicing. She created AI agents for personal tasks, reducing work that previously took days to under an hour. This hands-on experience transformed from a side project into a central career focus.
Giri observes stark differences in work culture across the three tech giants. Meta’s codebase is more straightforward, with Facebook, Instagram, and WhatsApp built from a single repository. Amazon’s massive codebase presents a steeper learning curve. Microsoft operates at massive scale with an enterprise focus.
Crucially, Giri views AI as a coworker, not a threat, noting that AI excels at repetitive tasks while humans monitor and guide it. She observes that demand for AI roles is skyrocketing while traditional software engineering positions have shrunk over five years. Many of her non-AI friends have struggled to find new opportunities.
For aspiring AI professionals, Giri recommends dedicating just one hour daily to learning, predicting visible progress within six months. Her recommended resources include 3Blue1Brown on YouTube, Fast.ai for project-based learning, Andrew Ng’s Machine Learning course on Coursera, Towards Data Science on Medium, and The Batch newsletter.
Key Quotes
I see AI as a coworker, not a threat. AI excels at repetitive or static tasks, and our job is to monitor and guide it. Managing AI, I believe, is the future of software engineering.
Nandita Giri, senior software engineer at Microsoft, explains her perspective on AI’s role in the workplace. This matters because it reframes the common fear of AI replacing jobs, instead positioning AI management as the next evolution of software engineering careers.
Demand for AI roles is skyrocketing, while traditional software engineering roles have shrunk over the last five years. Many of my friends who don’t work in AI have struggled to land new offers.
Giri observes the dramatic shift in the tech job market based on her experience across Amazon, Meta, and Microsoft. This quote highlights the urgent need for software engineers to develop AI skills to remain competitive in the evolving job market.
Tasks that used to take me a day or two can now be completed in under an hour. Seeing those results motivated me to keep learning.
Giri describes the practical impact of her self-taught AI skills on personal productivity. This demonstrates the tangible benefits of AI adoption and explains why she invested time in learning these technologies outside of work hours.
I recommend dedicating just one hour a day to learning AI. Within six months, you’ll see real progress, and these skills will be critical for the next decade.
Giri’s advice to aspiring AI professionals emphasizes that AI skills are accessible with consistent, modest time investment. This matters because it provides a realistic roadmap for engineers looking to transition into AI-focused roles.
Our Take
Giri’s career trajectory offers a compelling case study in how AI expertise has become the differentiator in Big Tech careers. Her self-taught approach is particularly noteworthy—it demonstrates that formal AI education isn’t necessarily required, but curiosity and consistent practice are essential. The fact that she moved from Amazon to Meta to Microsoft, each time increasing her scope and compensation, validates the market premium on AI skills.
What’s striking is her observation about friends without AI skills struggling to find opportunities. This suggests we’re witnessing a bifurcation in the software engineering job market: those with AI capabilities are thriving with multiple opportunities, while traditional engineers face a contracting market. Her recommendation to invest just one hour daily is actionable and realistic, making AI upskilling accessible to working professionals. Microsoft’s focus on enterprise AI through products like Copilot appears to be attracting top talent who see the long-term potential in business-focused AI applications rather than consumer products.
Why This Matters
This story highlights a critical shift in the software engineering landscape where AI skills have transitioned from optional to essential for career growth and job security. Giri’s experience across three tech giants—Amazon, Meta, and Microsoft—provides valuable insight into how AI expertise directly correlates with increased compensation, responsibility, and career opportunities.
The observation that traditional software engineering roles have shrunk while AI positions skyrocket signals a fundamental transformation in tech hiring priorities. This matters for current and aspiring engineers who must adapt or risk obsolescence. Her self-taught approach demonstrates that AI skills are accessible to motivated learners willing to invest consistent time.
Most significantly, her perspective that AI is a coworker rather than a threat reframes the automation anxiety narrative. Engineers who learn to manage and guide AI systems will thrive, while those who resist adaptation may struggle. For businesses, this underscores the importance of upskilling existing talent and prioritizing AI literacy across engineering teams. The story also validates Microsoft’s enterprise AI strategy with products like Copilot, showing how AI integration is reshaping productivity and business transformation at scale.
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Source: https://www.businessinsider.com/senior-software-engineer-microsoft-ai-not-threat-2026-1