Nandita Giri’s professional journey from Amazon to becoming a senior software engineer at Microsoft is a testament to the increasing demand for AI expertise at major tech companies like Amazon, Meta, and Microsoft. Giri emphasizes the importance of self-learning in AI by recommending dedicating one hour daily to beginners entering the artificial intelligence field.
This article, based on an interview with Nandita Giri, a 32-year-old software engineer at Microsoft in Redmond, Washington, details her career path and experiences. Giri’s interest in problem-solving and mathematics began long before her entry into the Big Tech industry. She pursued her education at the National Institute of Technology in Kurukshetra, India, where companies like Amazon, Microsoft, and Google actively seek talent.
Upon being hired by Amazon straight out of college and relocating to Seattle in 2018 after passing rigorous analytical tests and problem-solving interviews, Giri embarked on her tech journey. Currently holding a prominent role as a senior software engineer at Microsoft, her proficiency in AI has become highly sought after.
Giri’s passion for problem-solving extended beyond job requirements. She honed her skills through platforms like LeetCode out of personal interest rather than solely for interview preparation. This enthusiasm led her to identify automation opportunities within Amazon and propose AI-driven solutions to enhance internal workflows and decision-making processes.
After a successful tenure at Amazon, Giri was approached by Meta for potential employment opportunities via LinkedIn. Despite not initially considering joining Meta, her skills paved the way for new possibilities in applied AI work. Transitioning to Meta provided her with an environment focused on developing intelligent systems using extensive data and infrastructure resources.
Following a seamless recruitment process, Giri commenced her role at Meta in 2022 before eventually transitioning to Microsoft the following year. Her move to Microsoft was motivated by a desire to contribute to enterprise-focused AI initiatives such as Copilot that align with her aspirations for impactful tool development.
Giri’s career trajectory underscores the importance of continuous learning and self-improvement. By dedicating time outside of work to study AI through various resources like YouTube tutorials and blogs, she expanded her skill set exponentially. Starting with personal AI projects that enhanced efficiency in tasks like email outreach, Giri progressed from novice to proficient in AI applications over time.
Embracing AI as a collaborative asset rather than a competitor, Giri highlights the significance of managing and guiding AI systems as integral aspects of software engineering’s future landscape. She notes the escalating demand for AI roles compared to traditional software engineering positions over recent years, emphasizing the criticality of acquiring AI competencies for future career prospects.
Giri encourages aspiring individuals to allocate just one hour daily towards learning AI fundamentals as it can yield substantial progress within six months. She recommends educational resources such as 3Blue1Brown on YouTube for visualizing neural network concepts and Fast.ai for practical model-building exercises. Additionally, courses like Andrew Ng’s Machine Learning on Coursera and informative platforms like Towards Data Science and The Batch by Andrew Ng are valuable tools for beginners navigating the world of AI technology.
In reflecting on her professional journey, Giri advises prioritizing impact over perfection, taking early ownership of responsibilities, fostering confidence in communication, and emphasizing continuous learning and growth above all else as key components for sustained career advancement.