This is an interview with Sophia Willows, Head of Engineering, Rye.
Welcome to TechBullion! Can you tell our readers a little bit about yourself and your journey in the tech world?
I’m Sophia Willows, currently the Head of Engineering at Rye, a tech startup focused on building e-commerce APIs. My journey in the tech world started in Hamilton, New Zealand, where I developed a passion for technology and engineering. Before joining Rye, I was an Engineering Manager at Crimson Education, where I helped spearhead AI-driven solutions in the education space.
At Rye, we’re on a mission to simplify and accelerate how companies build e-commerce solutions by offering powerful, flexible APIs. I’ve always been driven by a desire to solve complex problems with innovative tech, and I’m particularly passionate about creating tools that developers love to use—something I’ve carried through my work at both Crimson and Rye.
I’ve also been fortunate to be recognized along the way, including a recent award in the ‘Technical’ category at Reseller News’ Women in ICT Awards here in New Zealand, which was a huge honor. Looking forward, I’m eager to continue pushing the boundaries of what technology can achieve and making it more accessible for businesses globally.
What pivotal moments or decisions led you to your current role in the tech industry?
Early on in my career, I knew that I wanted to work on impactful, cutting-edge projects. That meant being picky about the opportunities I took on. It doesn’t matter how brilliant you are as an individual if the things you are working on aren’t moving the needle.
Joining Crimson Education was one big moment in my career. I had a number of offers on the table, but I believe very deeply in education’s ability to transform lives and felt Crimson was truly pushing boundaries in that space. Leading their AI initiatives allowed me to work on meaningful solutions that directly impacted hundreds of students around the world, which was both incredibly rewarding and set me up well for future opportunities.
Can you share an experience where you had to overcome a significant technical challenge? What did you learn from that experience that you still carry with you today?
At Crimson, I oversaw the development of a suite of personalized recommendation engines for students using our services. These do things like suggesting extracurricular activities a student could engage in to boost the strength of their profile for college admissions.
There were two things that made this really difficult. The first was data complexity: we collected a lot of data about our students and wider industry trends, but it wasn’t stored in a central location, and the data itself came in a wide range of formats, making it difficult to use. We had to do a lot of groundwork to consolidate and clean the data before we could even start building useful models.
Setting up robust data pipelines is notoriously difficult, and in a space like college admissions, where the best practices change from year to year, it was essential that the infrastructure I stood up would stand the test of time.
The second challenge was ensuring scalability. We leveraged a lot of generative AI technology for these projects, and, at the time we were building this out, OpenAI was experiencing a lot of scalability issues. One of the features I built needed to send about 140 prompts to OpenAI to generate a result, and doing this at scale caused high latency from OpenAI’s API. Students expected near-real-time feedback from our tools, so I had to get creative.
I optimized the way we batched prompts and made adjustments to how we structured the data being sent to OpenAI. I also explored ways to cache frequently used results, such as semantic caching. This allowed us to mitigate some of the latency issues and keep the system functioning smoothly, even under high demand. From this, I learned that when working with cutting-edge technologies like generative AI, you have to anticipate and design for potential bottlenecks, especially around scalability. Building in layers of optimization, redundancy, and fallback systems is crucial to maintaining performance at scale. It’s a lesson that continues to inform how I approach scaling challenges at Rye, where ensuring our APIs remain fast and reliable under heavy load is a top priority.
In such a rapidly evolving field, how do you stay updated with the latest technologies and trends, and how do you determine which ones are worth investing your time in?
I’m fortunate to have a rich professional network of movers and shakers, and simply staying in touch with people like that helps keep me in the loop about new developments passively. In addition to this, I also have a few key thought leaders and publications I keep my eye on. I think there’s a lot of noise in the industry, so it’s important to be selective with where you get your information. Staying informed without getting overwhelmed means being intentional about where you focus your attention.
When it comes to determining which technologies are worth investing my time in, I’m always guided by two questions: “Will this solve a real problem?” and “Will it scale?”
There are a lot of exciting technologies out there, but I think a lot of engineers over-index on technology when what really matters is the problems you’re solving for your customers. Nobody would ever describe their carpentry business as a “screwdriver” company, but that’s something we see often in the tech sector, especially with “AI” companies. They focus so much on the tool—AI, in this case—that they lose sight of the actual problem being addressed.
For me, staying focused on the problem ensures that the technology is a means to an end, not the end itself. It’s this approach that helps me decide which technologies to explore further and which ones to set aside.
What advice would you give to someone who is just starting their career in tech and wants to make a meaningful impact?
My first piece of advice would be to stay curious and keep learning. Technology is hard because it moves fast while also having incredible depth. It’s impossible to know everything, and if you stop trying to better yourself then you’ll end up falling behind. Don’t be afraid to explore different areas early on—whether it’s development, product, data science, or something else entirely. I’ve been able to play a part in solving product, design, and marketing challenges. Diversity of experience can help you stand out in the crowd.
Second, focus on solving real problems, not just using the latest tech. It can be tempting to chase the most buzzworthy technologies, but at the end of the day, the most impactful work comes from addressing real-world needs. Always ask yourself: “What problem am I solving, and why does it matter?” That focus will help guide your decisions as you navigate your career.
Looking back at your career, is there anything you would have done differently, and what advice would you give to your younger self entering the tech field?
I would have started blogging a lot earlier. I’m a strong believer in the idea of learning in public, and it’s been a huge force multiplier in my career. Blogging forces you to clarify your thoughts and really interrogate the things you think you know. By explaining concepts to others, I’ve found that it strengthens my own understanding and helps me identify gaps I might have overlooked.
Sharing my experiences and challenges publicly has also led to unexpected opportunities. I secured my current role at Rye from one of their recruiters stumbling upon my blog via Hacker News, which is pretty incredible. I remember reading a piece from Krzysztof Kowalczyk about the concept of “luck surface area,” and a blog is a phenomenal method for boosting that. Writing regularly has helped me build credibility and a voice in the tech community, and if I could start over again I’d begin writing sooner. You don’t need to be an expert to provide useful insight because there are new people joining the field every day who can benefit from your content.
Tech is often associated with innovation. Can you share an instance where you saw a truly innovative use of technology that inspired you?
In my second year of high school, one of my best friends gifted me his iPhone 4S when he upgraded to the iPhone 5. I was amazed by Siri. Voice assistants were cutting-edge tech in the first place, and having it run on a mobile phone felt like a glimpse into the future. The idea that you could interact with technology using just your voice—and have it respond with useful information—was incredible. I spent hours testing Siri, asking it all kinds of questions, and trying to understand how it worked behind the scenes.
What really struck me was how seamlessly it integrated into everyday life. Instead of typing or tapping, I could just talk to my phone, and it would perform tasks like setting reminders or sending messages. At that moment, I realized how powerful user interfaces could be when they felt natural and intuitive. It wasn’t just about the novelty of the technology; it was about how it could simplify and enhance the way we interact with the digital world.
That early experience with Siri fueled my curiosity about AI and how technology can improve human-computer interaction. It also reinforced the idea that true innovation is about making technology more accessible and intuitive for users. That mindset has stayed with me throughout my career, whether I’m working on building APIs or designing products that developers—and their users—will love.
Many people are talking about the ethical implications of certain technologies. What are your thoughts on this, and how do you think we can ensure technology is developed and used responsibly?
Technology is a unique field in many ways. People working in tech often have access to incredible earning potential, and compared to other industries, the barriers to entry can be relatively low. You don’t necessarily need an advanced degree to make a meaningful impact—many successful developers and engineers are self-taught or come from non-traditional backgrounds. This accessibility is a very good thing; technology has uplifted people all around the world into the middle class.
At the same time, there’s a striking lack of accountability or liability for the systems we build, which is something that needs to be addressed. Software engineers are simply not held to the same level of scrutiny as other professionals are. When a civil engineer designs a bridge or a building, they’re responsible for ensuring it’s safe and structurally sound—lives are quite literally on the line. If something goes wrong, there are serious legal and professional consequences. In tech, however, software failures can have widespread consequences—think of data breaches, algorithmic discrimination, or AI mistakes—but those responsible often face few, if any, repercussions.
This disparity creates a challenge for the tech industry. We need to start holding ourselves to higher standards, especially as our systems become more integrated into critical aspects of society. Whether it’s designing software for healthcare, financial systems, or AI that makes decisions impacting real lives, the stakes are high. I believe that introducing stronger accountability measures—whether through industry standards, certifications, or regulation—will help ensure that we are building technologies that are not only innovative but also responsible and ethical.
We’re in a position of immense privilege, and with that comes the duty to ensure that our work benefits society and minimizes harm. Just as civil engineers build infrastructure that keeps people safe, software engineers should be responsible for the safety, fairness, and integrity of the digital infrastructure we create.
At the end of the day, technology should empower people, not exploit them. We need to balance innovation with responsibility, ensuring that we’re always working towards a future where technology serves humanity in a fair and sustainable way.
What are your predictions for the future of tech, and what advice would you give to those looking to thrive in this ever-evolving landscape?
The future of tech is incredibly promising, and I believe we’re on the cusp of breakthroughs that will significantly reshape how we live and work. Advancements in artificial intelligence, quantum computing, biotechnology, and renewable energy are likely to accelerate. AI will become more integrated into everyday applications, not just enhancing efficiency, but also enabling personalized experiences across various sectors like healthcare, education, and commerce.
One prediction I have is that technology will become even more democratized. Low-code and no-code platforms, along with more accessible learning resources, will empower an even broader range of people to build and innovate. However, this growth comes with challenges, including ethical concerns, job displacement, and security issues.
For anyone looking to thrive in the future, my advice would be to stay adaptable and focus on high-leverage skills. A lot of our day-to-day grind will be increasingly automated by AI, which means that skills like turning a design into a React component will become less valuable over time. Instead, focus on skills that allow you to drive change, lead teams, and think strategically—things that AI can’t easily replace. Understanding how to build systems, lead people, and solve complex problems creatively will set you apart.
I’d also encourage people to think about the ethics of the technology they’re building. Being mindful of the social, environmental, and personal impact of your work will not only make you a better engineer, but also a more responsible one. As technology becomes more powerful, so too does our responsibility to use it wisely.
