While specialized technical knowledge is often required for many AI and ML roles, AWS builders in this space stressed the importance of continuously honing your soft skills. Amazon’s 16 Leadership Principles provide a glimpse into our work culture, which has guided Amazon and AWS to build countless innovations over the years. AI and ML innovation is no different.

Roger Dahlstrom, a senior solutions architecture manager for AWS’s GenAI Labs, said some of the skills that are really important for generative AI roles are not technical at all.

“Some of them are being imaginative, some of them are being able to embrace ambiguity, some of them are being able to suspend thinking that something is impossible,” Dahlstrom said. “Some of them are being able to formulate instructions really, really well, which is not a purely technical skill.”

AI/ML enabled Ashley Gordon, a senior marketing manager for strategic accounts, to retain her passion for mission-driven work while opening a new world of career possibilities. She previously worked in the nonprofit world, telling the stories of more than 300 chimpanzees for scientific research. Then she discovered she could continue to pursue her mission-focused efforts by helping people around the world through technology.

“I encourage individuals to really step forward in their imagination to prove that they can have an incredible career,” she said. “What I have found is that AWS has afforded me plenty of opportunities to help people know more about technology, but also to change people’s lives.”

One of Amazon’s Leadership Principles is Learn and Be Curious, which highlights the need for successful leaders to never stop learning and always seek to improve themselves. It’s a characteristic that hiring managers look for when interviewing candidates because it’s essential to Amazon’s Day 1 culture and continuous innovation.

“We’ve recruited talent that has the ability to learn and quickly pivot to new challenges, and I think that’s really one of the best things about AWS. We focus on what you can do in the future, particularly when that future is unknown or uncertain,” said Brooke Jamieson, a senior developer advocate in AWS Developer Relations. “If you have the ability to learn new skills, develop new capabilities quickly, it's a super exciting place to be because you can ride that wave as it is developing.”

Jamieson is passionate about sharing her thirst for knowledge with others, too. She has authored blogs about "the ABCs of Generative AI" and "How to Learn Generative AI from Scratch" to help other builders unlock their curiosity and potential.

Diego Socolinsky, a senior applied science manager on the AWS Generative AI Innovation Center team, said that learning new skills and developing new talents are part of what makes AWS such an inspiring place to work and grow your career.

“My team members are not just constantly learning new things because they're interested, but they're also constantly sharing them with each other,” he said. “I find that my team are my teachers. I learn from every single one of them every day, and I know they learn from each other every day. If one of my teammates recommends something for me to look at or to read, it's almost guaranteed that's going to be useful and interesting.”

Some find their way to AI/ML by viewing new challenges as opportunities. That’s how Bianca Buckridee evolved her career from a bank call center to kindergarten teacher to financial services before landing in the AI/ML space. She now oversees marketing for the AWS Generative AI Innovation Center.

Taking risks and pushing through fear enabled her to launch innovative social media customer service applications in the banking industry.

“I would say pushing through your own fear is probably the most important part of this all,” she said. “You can do it, sometimes you just have to really force yourself to get in there. For me, my guiding principle is, ‘if it terrifies me, I absolutely have to do it.’ That’s what I recommend—find the way to push through that fear.”

The excitement of groundbreaking innovation is what attracted Sam Lisowski, a senior account manager for Gen AI Startups, to pursue an AI/ML career path. She studied an entirely different domain in school—Spanish writing and marketing—but her stepfather encouraged her to get into tech.

“He pulled me aside and said, ‘Sam, you’re an incredibly curious person and you’re always looking to dive in further,” she said. “I joined Amazon because I was looking to further explore technology and mentorship, be at the forefront of innovation, and with a large provider that was disrupting in the tech space.”

Dahlstrom also points out how well AWS is structured for career growth. He’s held multiple roles since he first joined AWS as a solutions architect in the enterprise space. He then went on to help build the AWS Data Lab, and from there helped start the resident architect program. Now, he’s one of the builders behind the AWS’s Gen AI Labs.

“If you want to build a career in generative AI at AWS, there are some skills everybody needs. One is to understand and embrace our Leadership Principles, which really are the way that we conduct ourselves and our business—from Earning Trust to Customer Obsession and all the others,” Dahlstrom said.

He recommends showing a willingness to be curious, embrace ambiguity, and really show that you can invest in yourself and learn. These are strong indicators that someone's going to be successful at AWS.

“Throughout my career at AWS, it’s been really seamless and fun to try that new thing—and skate where the puck is going—to keep on top of your career,” he said. “Keep investing in yourself, and trust that AWS is going to invest in you, as well.”