5 entry-level tech jobs AI is already augmenting, according to Amazon

Amazon today published a blog post by Michelle Vaz, managing director, AWS Training and Certification, that contains some fascinating insights about how AI is changing the landscape for people early in their careers.

To understand this dynamic, Amazon partnered with Draup, a "data intelligence firm specializing in workforce planning and talent analytics." Together, the two companies conducted a study entitled, "The Evolution of Early-Career Technical Roles in the AI Era."

Amazon hasn't yet provided us with all the data from the study, so I'll make some inferences. Amazon uses the term "early-career professionals," so the AI-related observations are likely about knowledge workers, not all new entrants into the workforce.

Also: Amazon's Andy Jassy says AI will take some jobs but make others more 'interesting'

The analysis raises the same concerns we've been discussing here on about AI potentially replacing entry-level jobs. On the other hand, Amazon's numbers show there is also considerable growth in demand for technical skills.

That paradox is something Vaz explores. She reports that young adult unemployment is at 6.6%, the highest in the past 10 years -- outside of the pandemic. According to the US Bureau of Labor Statistics, the overall unemployment rate was 4.1% in June and has been fairly steady for the past year.

One startling result from the study is this: 50 to 55% of "early-career workloads are now AI-augmented." In other words, it's not that AI will impact the workforce. It's that it is already having an outsized impact right now.

But what does this mean, at least for entry-level tech jobs? That's next.

AI is transforming entry-level tech work

Compared to the concerns I've recently been writing about, Vaz has a different, and potentially more encouraging, take on the impact AI has on entry-level roles. It's possible that both of us are right.

My observation has been that AI tools, particularly in tech and coding tasks, seem ideally suited to replacing the kinds of entry-level technical skills jobs that new employees have traditionally used to gain early-career experience. My postulate is that this could lead to a situation where there is a reduced workforce of people trained and ready to move from entry-level to mid-level jobs.

Vaz takes a different approach. She contends that AI will help those early in their careers punch above their weight class in terms of their skills. Those with lesser skills will be able to augment their performance with AI, which Vaz suggests will make technical roles more accessible to new career starters.

Also: 15 new jobs AI is creating - including 'Synthetic reality producer'

The blog uses an interesting phrase that showcases both an opportunity for newcomers and a threat for those who have spent a career building their skills. She says, "AI-assisted tools are democratizing tasks that once required years of experience, creating new opportunities across the tech industry."

For those early in their careers, AI support will require workers to regularly incorporate more complex thinking and handle projects of greater magnitude. For those able to keep up, new or early-stage employees will be able to make strategic contributions right from day one.

Five high-growth tech roles being redefined by AI

It's hard to tell if this is face-saving hype propagated by one of the nation's largest and most controversial employers, or whether this marks a seminal inflection in labor history. Only time will tell. Vaz says that Amazon's research identified five highly technical roles where entry-level employees are able to use AI to hit the ground running.

She also says that Amazon's research indicates an increasing rate of growth in demand for people qualified for those jobs.

Also: AI could erase half of entry-level white collar jobs in 5 years, CEO warns

Unfortunately, while her blog post indicates growth rates and job postings for each career area, it doesn't indicate the source of the posting listings, nor where the growth rate data is sourced from. Because the absolute job-availability numbers she lists are so large, I don't believe this data comes from Amazon's own internal hiring demands, but where it does come from is unclear.

Amazon provided some background on how the data was derived. The company told me:

Draup used a multi-step methodology to conduct this research. 

• First, they identified in-demand early-career roles accessible to both STEM and non-STEM graduates by analyzing global job postings across industries with high cloud adoption. 
• Second, they mapped these roles to real-world AI and cloud use cases to contextualize how technologies are applied in workplace settings. 
• Third, they connected identified roles to relevant AWS Skill Builder learning paths, creating focused upskilling pathways that address gaps in university curricula. 
• Finally, they applied a Job Role Attainability Model that assesses how accessible roles are for new graduates based on skill proximity and role complexity.

Very cool. With that, let's look at each of those careers.

1. Software development

As much as we've been sharing our concern about future job prospects for entry-level coders, the Draup/Amazon study reports that there are 283,000+ entry-level job postings, indicating a 28% annual growth from June 2024 to June 2025.

The study reports that, contrary to expectations, entry-level developers are in demand. The difference is that instead of spending hours on basic coding, these entry-level workers are expected to use AI to work on more complex projects right from the start.

Also: Open-source skills can save your career when AI comes knocking

The only issue I have with this is that it doesn't seem to line up with the widely anecdotal accounts of so many entry-level developers who are trying and failing to find jobs. Reconciling this report with those stories is not entirely possible, so again, we'll need to see how all this pans out.

2. Data analysis

The Draup/Amazon study shows that data analysis is also in high demand, reporting 125,000+ postings and a 16% growth rate. Since AI automates data-prep tasks previously assigned to juniors, the new hires can focus on generating business insights and strategic analysis using AI-assisted tools.

3. Cloud engineering

According to the study, 90% of the workloads managed by entry-level IT professionals are cloud-centric. These are engineering-related tasks related to cloud-enabled architecture, like virtual machine maintenance, container orchestration, code-based infrastructure, CI/CD pipelines, storage and compute services, serverless functions, and so on. The study reports 45,000+ postings with a 9.5% year-over-year growth.

4. Cybersecurity

As threats increase, cybersecurity becomes more challenging and demand for staffing grows. Even though AI-supported automated threat detection and mitigation is a key defensive measure in the ongoing arms race, there is still a 62.5% growth in demand for early-stage workers. Essentially, where hands-on experience was once critical for job performance, the AI support can help beginners mitigate problems fairly soon out of the gate.

5. Data engineering

Data engineering differs from cloud engineering in that data engineers focus on building and maintaining data pipelines that move, transform, and store data for analysis or applications, while cloud engineers focus on managing cloud infrastructure.

Likewise, data engineers focus on preparing raw data, bringing it in, validating it, and structuring it, and then focusing on pipelines, warehouses, and efficiency. Data analysts use that data to look for insights and ask business-related questions.

Managing this pipeline of data becomes even more essential in an AI-focused world. The Draup/Amazon study shows 103,000+ postings with a 12% growth year over year, with entry-level personnel moving away from simple data crunching and into supporting more complex data-related tasks with the addition of AI help.

The rise of the AI-native professional

When I entered the workforce, I was a member of one of the first cohorts of digital-native workers. I entered the workforce with an already inculcated understanding of computers, productivity tools, and networking. This native, "built-in" understanding was in stark contrast to previous generations of workers, who were still coming to terms with a digital-first environment.

Today, we're seeing a new ontological bifurcation. Some of us are AI pioneers who have been creating, learning, and adapting to various forms of AI for quite some time now. Compare that to the youngest worker generation, who have come of age in an AI-centric world in the last few years. These are incoming employees who may have only two or three years on the job, but all those years were assisted by generational AI tools.

Also: 60% of managers use AI to make decisions now, including whom to promote and fire - does yours?

Vaz describes these new workers as "individuals who enter the workforce ready to collaborate with AI tools to drive innovation and solve complex problems from day one." They embrace tools that amplify their capabilities right from the start.

This, of course, can sometimes be a problem. Over-reliance on AI can cause all sorts of disruption, both in terms of simply bad advice to issues of ownership and plagiarism due to the training methods of the AIs. For example, does not allow any of its writers to use AI in the process of creating articles -- with the obvious exception of testing out and reporting on AI capabilities.

Even so, with more AI-comfortable workers entering the workforce, the ability for AI to force-multiply will be less of an outlier and new thing, and more just simply de rigueur for all employees.

Amazon investments and initiatives for workforce development

Concurrent with today's blog post is a big announcement coming out of the AWS New York Summit. Amazon is making some serious investments in workforce development. Here's a quick list of all the initiatives they're kicking off today.

In terms of AWS investment and access, the company has announced a $3 million initiative to train what they hope will be 2.7 million learners. They're also offering free access to AWS Skill Builder and certifications via AWS Academy. Amazon reports that more than 6,600 institutions are using AWS teaching resources globally, plus they're making access to hundreds of free courses to self-learners unaffiliated with educational institutions.

The company has also announced hands-on learning tools. Tools like AWS Cloud Quest and Simular provide scenario-based learning that simulates real-world challenges in cloud computing and generative AI. Additionally, the AWS Builder Center offers targeted career guidance for key roles.

Also: AI agents win over professionals - but only to do their grunt work, Stanford study finds

Amazon is also announcing the AWS AI League, which is a competitive learning platform inspired by their fun AI training toy, DeepRacer. The company is starting with two tracks. Prompt Sage will foster prompt-engineering mastery, while Tune Whiz will help participants learn to fine-tune AI models for business needs.

Included are all the trappings of a good competition, including live leaderboards, expert judging, and $2 million in AWS credits, as well as a real-money $25,000 prize pool. The challenges are designed to foster real-world problem solving for industries like finance, healthcare, and more.

Redefining early careers in the AI era

To some degree, it's hard to tell how much of this is Amazon performing workforce theater.

After all, with their recent announcement about replacing workers with AI, getting some positive PR about investment in workforce skill building is good for the company's image.

On the other hand, Amazon is one of the most effective logistics operations in human history, and the workforce is a critical component of any logistics operation. So investing in gaining a deeper understanding of how workforces will evolve in an AI-centric world does make a great deal of sense. It's not only to the benefit of future workers and employers, but to Amazon's logistics operations themselves.

Also: How AI can save us from our 'infinite' workdays, according to Microsoft

Overall, I see this as a good thing. But it does leave us with an interesting question. Going forward, what does entry-level even mean? This new take on AI assistance shows that AI may give less costly entry-level workers an advantage over those with more experience who are later in their careers.

If AI is so amazing and empowering, why do I always feel slightly nauseous after writing one of these future-looking AI articles?

What about you? Are you seeing AI reshape your own early-career path or helping others get a head start? Do you think AI is truly democratizing opportunity, or just moving the goalposts? Have you explored tools like AWS Skill Builder or participated in any competitive learning programs like DeepRacer or AI League? And what do you think it means to be "AI-native" in today's job market? Let us know in the comments below.

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