As the 2025-26 academic year draws to a close, a new cohort of graduates is entering a job market increasingly defined by the intersection of education, science, and technology. For many, the fields of ed tech and learning engineering offer an exciting opportunity to innovate and contribute positively to society, but breaking into the field can feel daunting. The perceived complexity of research, data science, and technical architecture can make the work seem inaccessible, especially to those without a traditional technical background.
However, while there is some need for technical skills, many argue that an understanding of the human side of the equation – specifically, identifying where technology supports learning and where it creates friction – is often a missing skillset that is prized by ed tech developers and employers.
Krishna Chaitanya Rao Kathala, Program Director for the Transitional Data Analytics Institute at The Ohio State University, believes this is one of the best times to enter the field.
“The most effective entry point is to become deeply knowledgeable about a real educational problem,” Kathala said, pointing to areas like student engagement, assessment, tutoring, feedback systems, or accessibility. “Domain understanding is becoming just as valuable as technical depth.”
To help the next generation of ed tech innovators break through, a network of experienced learning engineers, researchers, and industry leaders offered their ideas on how early-career candidates can stand out. Here are the eight top tips they shared for landing your first ed tech role.
1. Translate Your Experience Into Ed Tech Terms
Many recent graduates may feel they lack “relevant” experience because they haven’t held a formal title in education or technology. However, experiences gained through tutoring, peer mentoring, or student leadership are highly transferable when viewed through a functional lens. To stand out, you must reframe these activities as product and engineering outcomes.
For example, if you tutored a fellow student, you weren’t just “helping”; you were identifying learning gaps and personalizing instructional content. If you led a campus organization, you were managing a project lifecycle and balancing stakeholder expectations. Even helping a peer troubleshoot a new app is a form of technical onboarding and user support. Translating your experience in this way signals to hiring managers that you understand the mechanics of the learning process and can apply that knowledge to the real-world problems their products aim to solve.
2. Teach to Understand The "Friction"
The most fundamental piece of advice from veteran learning engineers is also the most practical: teach. By putting yourself in front of a group of people trying to master a new concept, regardless of the subject, job candidates gain a first-hand perspective on where the learning process actually breaks down.
Jordi Rosquillas, Digital Strategy Director at the Center for Strengthening Civil Society, said that this experience is essential for identifying “friction points” – those specific moments where a student becomes stuck or frustrated. In ed tech, these insights are invaluable. Understanding where a learner struggles allows you to see where technology can provide a genuine solution and, conversely, where a digital tool might actually become an obstacle to understanding.
Aly Murray, Founder and Executive Director of UPchieve, echoed this idea, calling a few years in the classroom “one of the most underrated paths into ed tech.” Murray noted that a teaching background isn’t just viewed as a career pivot, it is seen as a distinct bonus for any role within the company. For a recent graduate, the ability to articulate classroom nuances during an interview demonstrates a practical pulse that a resume alone cannot convey.
Understanding where a learner struggles allows you to see where technology can provide a genuine solution and, conversely, where a digital tool might actually become an obstacle to understanding.
3. Focus On Human Interaction Over Pure Code
As generative AI begins to automate routine aspects of software architecture and deep coding, the most critical skill for a recent graduate is an understanding of the human side of the equation. Rather than becoming bogged down in the intricacies of backend development, candidates should lean into how humans actually interact with technology – the psychological and motivational factors that drive learning.
Rosquillas noted that while AI is shifting some entry-level programming positions, the core acts of learning and teaching remain profoundly human.
“Put yourself in a position where you can observe AI in action, identifying specifically where it helps or hinders the learning process,” he said.
By focusing on the human element, such as how a student’s mental workload is managed, you develop a specialized expertise that remains vital even as the underlying technology changes.
Kathala emphasized that as routine technical tasks are automated, the job market will strongly favor these cross-disciplinary skills.
“The future will favor translators,” he said. “People who can connect educators, researchers, engineers, and organizations.”
He added that the value employers look for in employees is shifting away from raw coding and toward the ability to frame complex problems and evaluate AI systems responsibly.
“The future will favor translators,” he said. “People who can connect educators, researchers, engineers, and organizations.”
4. Dedicate Time To Building "Hard Skills" And Learning The Landscape
While networking and other soft skills are essential, technical roles still require targeted, focused study. Transition periods like the months following graduation, provide a unique window for this kind of learning that is often difficult to manage while working a full-time job.
If you’re interested in a technical role, treat this transition period as a strategic opportunity. Instead of trying to master deep backend software development, focus on applied skills like data visualization, prompt engineering, or learning analytics through targeted courses, many of which can be taken online for free or at a low-cost.
It is crucial that this foundational literacy is paired with an understanding of the market ecosystem. Murray emphasized that knowing the broader educational landscape is just as vital as mastering data. She advised new graduates to immerse themselves in active industry research.
“Read – a lot,” she said. “Read about ed tech products already out there, read learning science research, read education publications, and sign up for newsletters.”
Dedicating blocks of time to both technical fundamentals and understanding the context of industry tells employers that candidates possess both the drive to build and the context to know what needs building.
As Murray noted: “The people who stand out in this space aren’t always the ones with the most experience; they’re the ones who show up already knowing the landscape.”
“The people who stand out in this space aren't always the ones with the most experience; they're the ones who show up already knowing the landscape.”
5. Prioritize Applied Contexts Over Formal Training
Once you have built a set of foundational skills, the next step is to test them in the real world. While technical degrees provide a great framework, early-career success in ed tech is driven by practical application. For a recent graduate, this means moving beyond theoretical models and seeking out roles, internships, or volunteer projects that give opportunities to work with live users and real data.
Employers want to see that new hires understand how tools are implemented and evaluated in the noisy, unpredictable environment of an actual school, backyard tutoring program, or corporate training setup – rather than just in a controlled academic study.
6. Seek Interdisciplinary Collaboration
Learning engineering does not exist in a vacuum; it thrives at the intersection of research, product development, and classroom practice. For those entering the field, the most effective way to build expertise is to move beyond a single discipline and find projects that require cross-functional teamwork.
Natalia Kucirkova, Professor and Director of the International Centre for EdTech Impact, referred to this as the “Golden Triangle” – a model where researchers, developers, and educators all have an equal voice in the design of a tool. For a recent graduate, a practical entry point is to join organizations, open-source communities, or university labs that intentionally bring these three networks together. This way, new grads can learn how to translate a researcher’s data into a developer’s feature, or a teacher’s feedback into a product update.
7. Master The "Build-Test-Iterate" Cycle
The most valuable asset a job candidate can bring to an ed tech team isn’t proficiency in a specific programming language; it is mastery of the design process. Employers look for candidates who can identify a problem, brainstorm a solution, build a prototype, test it, and improve it based on feedback.
Kristen DiCerbo, Chief Learning Officer at Khan Academy, emphasized that demonstrating an understanding of this cycle is more important than the specific tools you use.
“We are looking for people who have gone through the process of identifying a problem, brainstorming solutions, settling on one, building, testing, and iterating,” she said. “What did they learn about the process? With vibe coding so easy now, anyone can do this.”
By testing a prototype with actual users and documenting how user feedback resulted in design change, a job prospect can show that they can manage the messy, non-linear reality of product development.
“We are looking for people who have gone through the process of identifying a problem, brainstorming solutions, settling on one, building, testing, and iterating. What did they learn about the process? With vibe coding so easy now, anyone can do this.”
8. Embrace The "Blurring" Of Professional Roles
DiCerbo also noted that the old walls between product management, design, and engineering are crumbling. Today, the most competitive candidates are “hybrid” professionals – people who are comfortable stepping outside their exact job descriptions to keep a project moving.
This flexibility is a distinct advantage. For example, a product manager who can use AI to build a quick prototype, or a designer who understands basic coding constraints, is far more valuable than someone who stays strictly in a single lane.
While AI might mean fewer traditional entry-level job openings, it also changes how companies judge talent, potentially leveling the playing field for newcomers. Because AI tools allow one person to handle multiple types of tasks, Murray noted that a sharp recent graduate can perform just as well as someone with years of experience, both on the job and in the interview process.
In this new environment, employers care less about chronological tenure on a resume and more about how you think.
“Quality of strategic thinking will begin to matter more than years of experience,” Murray said. For a recent graduate, the takeaway is clear: don’t specialize too early. By learning the basics of the roles around you, you become a versatile collaborator and a much safer bet for companies hiring in a fast-moving market.
For a recent graduate, the takeaway is clear: don't specialize too early. By learning the basics of the roles around you, you become a versatile collaborator and a much safer bet for companies hiring in a fast-moving market.
Conclusion: Engineer Your Own Path
The “perfect” ed tech candidate isn’t necessarily a computer science expert. Rather, they are someone who thrives at the intersection of human cognition and product design. While AI increasingly handles the technical backend of many learning tools, the demand for professionals who understand pedagogical friction and human interaction has never been higher.
To land that first role, new grads should treat their job search like a learning engineering project: identify the roles they want, test their “translated” resume, and iterate based on the feedback they receive from the market. Candidates don’t need a specific job title to begin the work. By observing learners, testing tools, and embracing the build-test-iterate cycle, they can demonstrate the exact interdisciplinary skills the industry needs most.
