- Supreet Kaur received a job offer from Microsoft after interviewing with 15 companies.
- After working in AI at Morgan Stanley for two years, Kaul noticed a big shift in the market for AI-related roles.
- She emphasised the need for LLM experience, networking and understanding the AI needs of enterprises.
Supreet Kaur, 29, has just received an offer from Microsoft after interviewing with 15 companies in the past few months.
Prior to her new role, she spent the past two years developing and managing data and AI solutions at Morgan Stanley. She says the job market for AI-related roles has changed significantly since she began her job search about two years ago.
While CEOs of major tech companies are vying for AI talent, other candidates are also vying for a place in an increasingly competitive job market.
Kaur has a graduate degree in data science, works in AI at a major bank, and is an ambassador for Google's WomenTechMakers program, but she said she didn't hear back from companies when she first started looking for jobs.
After tweaking her approach a bit, Kaur began to see results, ultimately landing a job as a cloud solutions architect at Microsoft. If you're looking for an AI job, Kaur shares four key things to know:
LLM experience is now the industry standard
Kaur said when she interviewed for AI roles two years ago, companies were looking for experience with machine learning, but now they're looking for people to build AI products. They care more about candidates having experience working with chatbots or text classification systems, she said.
Kaul said that while experience in generative AI or a master's in law is now the basic criteria, he didn't get called back for interviews until he had developed skills in the field.
Knowing this is what many recruiters are looking for, Kaul volunteered with an organization and completed a three-month project for her Master of Laws degree. While many applicants looking to enter the field now attend AI workshops and bootcamps, Kaul suggests doing a use case project. Kaul used her volunteer experience to create her own enterprise-level project so she could talk about it in detail during the interview.
Cold application may not work this time
Kaur said she didn't send out many applications, but she didn't get a response from the ones she did send out. Instead, she spent her time networking and reaching out to recruiters, with the goal of sending at least two messages and three to four personal connection requests every day.
She also sought to publicize her job search by telling professional contacts that she was looking for work.
“The best way to find work is when you don't need a job,” Kaul said. “Go to events. Go to meetups.”
specifically
Kaul said the mindset of companies has changed over the past few years and they are now looking for more tangible experience.
“When I interviewed in 2022, people were more interested in what I did in the data science field,” Kaul said.
“This time around, every interview I had was very specific about what the companies were looking for,” she added.
With corporate recruitment portals overflowing with qualified applicants, Kaul said he had to narrow his focus. He said he realised his first attempt was too broad and narrowed his focus from product managers to solution architects.
Kaul also recommends networking with employees at the companies you're applying to and asking them what they're looking for, which she says is crucial to understanding their needs and what specific experience they're looking for in candidates.
Having an online presence
Kaul has also been working on growing her online presence over the past few years.
She said she has spoken at dozens of events, many of which led to subsequent interviews, and that it also helped her stand out during the application process.
“During my interview, one of the hiring managers said to me, 'You're the 100th candidate we've interviewed for this position,'” Kaul says. “Clearly the competition is fierce, so it's important to stand out.”
Kaur says she first reached out to her former university and let professors know she was available to speak to them about her experience. From there, she built a following and was regularly booked to appear at events like AI Summit New York, BNY Mellon, Re-Work New York, Women in Data Science Series, and Women in AI Series.
