AWS builders note we’re just beginning to understand what’s possible with generative AI.

"This technology breakthrough is revolutionary and is making us reimagine the future in every industry," said Suchitra Sathyanarayana, senior applied science manager at the AWS Generative AI Innovation Center. “It's an exciting moment to be in the middle of this at AWS.”

Sherry Marcus, Ph.D., director of Amazon Bedrock Science, calls this pace of innovation and milestone "a once-in-a-lifetime moment."

"At AWS, we're helping establish new technologies that will transform businesses,” Marcus said.

Brooke Jamieson, a senior developer advocate, said developers famously go through “hype cycles, but this generative AI one feels different.”

AWS customers range in size from small startups to multinational corporations and government entities, which creates a unique environment for tackling generative AI challenges.

“Our teams work with global enterprise customers spanning every industry vertical—from financial institutions to manufacturers to media and entertainment companies,” Socolinsky said. “If you're interested in working with giants in any industry vertical, our organization does that every day.”

Socolinsky's team at the Generative AI Innovation Center helps customers adopt and accelerate business value with generative AI.

"We work on problems important to the organization, and the solutions we develop get deployed to customers in a very short time frame,” he said. “The impact is tangible and timely.”

The world's best foundation models (FMs) are available on the Amazon Bedrock platform, AWS's fully managed service offering a choice of high-performing FMs from leading AI companies. AWS is building layers of abstraction on top of these models so that customers can determine which models are best for different use cases.

For those drawn to working at this scale, Isaiah “Zay” Steinfeld, director of startup acquisition, summed it up: "If you're a technologist, if you want to be in the middle of it — scale and pace — I think those are the advantages that AWS brings."

At AWS, employees aren't just theorizing about generative AI, they're taking their boldest ideas from concept to global deployment. The combination of cutting-edge tools, vast compute power, and a culture of empowerment enables even the boldest ideas to become reality.

"Everyone's excited about how it's changing the industry,” Jamieson said. “Not just the different things they can build, but the new tools to help build those things in different and more efficient ways.”

This excitement stems from AWS's ability to rapidly take concepts into production.

"We're unique in having the full stack needed to rapidly scale solutions into production, so you see impact very quickly at AWS," explained Anila Joshi, applied science manager at the Generative AI Innovation Center. "You drive an idea from inception to realization extremely fast on this team."

The entrepreneurial culture at AWS further fuels this spirit of innovation.

"I'd say Amazon is like the largest startup I've ever seen," Steinfeld said. "You have a front row seat to a shifting technology that is literally breaking, changing, and leapfrogging by the minute, week over week.”

“What I love about working at AWS is that there are so many brilliant people that you have access to, which you normally wouldn't have inside your network,” said Nashlie Sephus, Ph.D., a principal AI/ML evangelist on the AWS Responsible AI team. “If you’re interested to learn more about their role or what they're thinking, you can just send them a quick message and you're instantly connecting with them,”

The people making generative AI innovation possible are also “laying the groundwork for companies to use generative AI capabilities at transformative scales,” Marcus notes.

"You'll be working across many of the world's best large language and multimodal models, including AWS's own Titan models," she said. "You'll apply those models to solve real customer problems at massive scale, working with the best engineers, scientists, and product managers."

Responsible development lies at the core of AWS's approach to generative AI. Building trustworthy systems that avoid biases and potential harms is not just an ideal, it's a fundamental imperative.

Marcus emphasizes that AWS builds responsible AI principles into our development process from the start.

“We don't want to get this wrong, as it's essential that customers understand the systems we develop will be fair, unbiased, and non-toxic,” she said.

AWS takes a proactive, multi-stakeholder approach to responsibility.

"Responsibility is about making sure we develop this technology in a way that is safe for everyone and helps everyone to the same degree without bias," said Ashish Singh, software development director and general manager of AI services on the Amazon Bedrock team. “It's important to get it right for humanity.”

Isaiah “Zay” Steinfeld, AWS director of startup acquisition

Given AWS's entrepreneurial, startup-like culture, employees enjoy considerable ownership over their generative AI work.

"There's a lot of autonomy in how you make product decisions and operate the business,” Singh said. “The autonomy, independence, and impact you can have on customers are key ingredients for happiness here.”

At AWS, an employee can have an idea, building a playground for large language models, and watch it become a public-facing product used around the world, Jamieson said, referring to AWS's PartyRock as a recent example.

“If you have a good idea and are willing to fight for it with data and writing, you can build momentum like at a startup,” she said. “If you're ambitious, there are ways to work across verticals and technologies. If you have an idea and leadership support, you can create it.”

Working at the forefront of generative AI, continuous learning is essential for staying ahead of the curve. AWS provides robust training resources and an environment that encourages skill development.

"It's a very self-motivated organization, so having bias for action and ownership are important. The ability to constantly learn new skills is critical, which happens in a self-motivated way," Socolinsky said. "My team is always learning from each other."

As we imagine and reimagine what we can accomplish in every walk of technology, employees emphasize the importance of maintaining a curious mindset.

"AWS looks for talent who can learn and pivot to new challenges quickly, since we can't always anticipate what skills will be needed in the future," Jamieson said. "The ability to learn new skills and develop new capabilities rapidly is really valuable."  

AWS employees work on leading generative AI solutions with the potential to drive positive impact across various domains, from healthcare to sustainability.

"The amount of things that I'm able to experience, working with the customers that I work with, is something I'll never be able to experience anywhere else," said Shane Thompson, senior startup solutions architect, AI/ML.

"I went from nonprofit public relations and marketing to AWS, thinking I'd have to give up mission-driven work. But AWS has allowed me to still help people through technology," said Ashley Gordon, senior marketing manager, strategic accounts.

As Thompson put it, "The reason I work in technology is because of the infinite possibilities, the number of problems that we can solve, things we haven't even thought of going forward, things we don't even understand about the way the world works. Those are all things that are going to be solved by technology. And that's why I'm passionate about what I do and why I love to work in this space."

Developing powerful, inclusive, and equitable generative AI solutions requires drawing from a multitude of backgrounds and viewpoints. AWS actively cultivates an environment of diverse perspectives. As Jamieson notes, "It's important we have diverse voices building these products, because we have such a diverse range of people using them.”

"Our teams are quite diverse in terms of skill sets — we have scientists with PhDs, but also those focused on architecture or software development from different backgrounds," Socolinsky said. "Having that variety brings diverse perspectives that we wouldn't otherwise get."

This diversity extends across roles, disciplines, and experiences, which often attracts new team members. Many are also excited to further uplift diverse voices.

"I'm very adamant about recruiting other diverse candidates for our tech teams," Sephus said. "If you think about it, it's all tied into responsible AI. The more diverse our tech teams are, the more different types of thoughts and backgrounds that go into the product, the better the product is."

If you're passionate about cutting-edge technology and want to make a real impact, we'd love to hear from you. Check out our open roles in generative AI and apply today.