How To Build a Career in the Age of AI

As Penn Engineers prepare for graduation, many are entering a dynamic and unpredictable labor market shaped by artificial intelligence, economic uncertainty and rapidly changing expectations for entry-level candidates. For early-career engineers, that can raise urgent questions: Which skills still matter? Which tasks will be automated? And how should graduates use AI without becoming overly dependent on it?

Jamie Grant (C’98, GEd’99), Senior Associate Director for Penn Engineering at Penn Career Services, works closely with students as they explore career paths and prepare for internships and full-time roles. In a recent conversation, she discussed how students can think about AI as an “exoskeleton” for their work, why foundational engineering skills still matter and how graduates can better communicate the full range of skills they have developed at Penn.

Jamie Grant has been carefully tracking the rise of AI as she helps prepare Penn Engineers for the workplace. (Credit: Sylvia Zhang)

Given the rise of AI, how are job responsibilities for engineers changing, especially for early-career engineers?

While national headlines declare that AI is erasing the entry-level job market, the story is more nuanced. It’s clear that the skills to leverage AI are becoming essential in the workforce, helping new grads to elevate how effectively and quickly they can work.

AI may allow an early-career engineer to do more than someone at the same career level might have done in the past, but it also heightens the need for accountability. If you save time by using AI to produce an analysis or draft an output, some of that time needs to go back into auditing, reviewing, validating and making sure you can speak to the work.

Asking questions like, Does the output make sense? Is it ethically sound? Is it relevant to the business or organization you are part of? The AI agents that most people use are not necessarily trained on or reliably and accurately accessing your company’s internal data, industry requirements or regulatory environment.

AI can speed up comparison, analysis and discovery in ways that would have taken human analysts years. But, in many long-standing industries, there are designs, systems, manufacturing processes, infrastructure and technical records still in use today and essential to business functions that may not already be digitized or part of any AI model’s training data.

This becomes especially important in highly regulated industries. If you are working in healthcare, a mistake could affect a diagnosis. In a business setting, it could have financial implications. In a legal context, it could have serious consequences. Students need to understand when using AI is appropriate, when it is not and how to vet what comes out of it.

Grant encourages students to use AI as a tool, while continuing to develop the practical skills and conceptual oversight that make engineering work reliable. (Credit: Sylvia Zhang)

In a recent article in IEEE Spectrum, you compared AI to an exoskeleton. How is Penn Engineering preparing students to use that exoskeleton?

An exoskeleton can enhance someone’s physical capabilities, but you still need to know how to wield it. Otherwise, there can be mishaps. That is where human judgment and conceptual oversight come in.

Penn Engineering students are in a strong position because many of their classes are designed  to create space for them to experiment with AI, especially with faculty who are using AI in research or developing AI tools themselves.

That approach also reflects the direction of Penn Engineering 2030, the School’s strategic plan, which emphasizes integrating AI tools and data-centric thinking across the curriculum.

That understanding matters. It is one thing to use a tool. It is another to understand how that tool accesses information from a large language model that was built, trained and informed, but that undoubtedly has limitations.

Fortunately, our students have opportunities to practice using AI in a relatively insulated environment. That includes not just coursework and research, but also student organizations like AI@Penn and Claude Builder Club at Penn, where students can experiment, build and learn before using these tools in higher-stakes professional settings.

Grant advises graduating engineers not to undersell their accomplishments, especially the initiative and creativity they have shown through hands-on work. (Credit: Sylvia Zhang)

What should students remember as they enter a competitive job market?

Every student who graduates from Penn Engineering has the talent and capacity to do amazing work out of the gate.

But students are entering a competitive professional world where employers aren’t taking credentials and degrees at face value and instead moving toward more skills-based hiring. That Penn Engineering degree is undeniably powerful, but even if it opens the door, students still need to be able to walk through it.

The job market is also affected by variables students cannot control: interest rates, tariffs, global supply chains, company hiring cycles, overhiring after COVID and the way major companies are quickly shifting resources toward AI. AI itself is easy to call out as a reason for a tighter entry-level labor market, but it’s certainly not the only cause.

That is why students need to be strategic. Entry-level jobs and career paths still exist, but they are changing. If, as a candidate, you can understand that change, adapt to it and articulate the value you bring, you will be in a much stronger position.

Grant encourages students to experiment with AI in classrooms, clubs and projects, where they can learn how to use these tools before applying them in higher-stakes settings. (Credit: Sylvia Zhang)

What is the most important advice you would give graduating Penn Engineers?

You are your most capable advocate; be sure not to undersell what you’ve already been able to accomplish.

Reflect on the skills you’ve developed and demonstrated — in classes, projects, teams, research, internships, clubs and independent work. Employers will not automatically know what those experiences taught you. You need to be able to explain the what, the how and the why.

Class assignments, while great examples of your skills in action, aren’t always the best indicators of your “why,” because they are pre-determined for you. Create your own why by thinking about problems you’d like to solve, considering projects you might take on and gaining experiences that also help you to demonstrate your initiative.

Again, AI may help you to work faster, to communicate more succinctly, to quickly analyze data, and using it as a tool — or even being part of building it — is essential. As AI improves, who knows what the future might hold? For now, it is your judgment, your ability to learn, your ethical awareness and your capacity to explain your own work where you can most certainly stand out.

Penn Engineering students and alumni can read more of Jamie’s advice and reach out to schedule an appointment with her online.

Topmost: Jamie Grant (C’98, GEd’99) speaks with a student in the Penn Career Services office (Credit: Sylvia Zhang).