Can you tell us about your role at Abnormal?
Sure. I act as the single-threaded owner of the Message Security Division, which means I oversee the team that builds machine learning solutions powering our inbound email security product. Our division is highly cross-functional, bringing together software engineers, machine learning engineers, data scientists, and analysts to develop solutions that protect organizations from cyber threats.

AI plays a huge role in what we do. We leverage machine learning to detect anomalies, filter out threats, and continually improve our models as new security challenges emerge. The scale at which we process information and detect threats would be impossible without AI-driven automation and intelligence.

How do you see AI evolving in security and engineering in the coming years?
AI is evolving rapidly, and its role in security is only going to become more critical. Right now, AI allows us to detect anomalies and respond to threats faster than ever before, but the future is all about making AI even more autonomous. We’re moving toward self-adapting security systems-models that don’t just react to threats but anticipate them before they occur.

I also see AI playing a huge role in improving efficiency for engineers. AI-powered development tools are already accelerating the coding process, debugging, and optimizing workflows. As we integrate AI more deeply into engineering, we’ll see smarter automation, better anomaly detection, and even predictive security measures that can help engineers stay ahead of cybercriminals. The goal is to make security proactive rather than reactive, and AI will be the key to making that happen.

What drew you to Abnormal, and what has kept you here?
I was drawn to Abnormal because of its strong technical culture and the opportunity to work on cutting-edge machine learning problems in cybersecurity. The challenge of tackling real-world threats at scale was compelling, and I saw an opportunity to grow both technically and as a leader.

What’s kept me here is the people. The engineering team is filled with some of the smartest, most thoughtful individuals I’ve worked with. There’s a deep culture of collaboration, and I appreciate how much autonomy we have in solving complex problems. We’re constantly iterating and improving, which makes every day exciting. Additionally, there is a strong support system here that encourages learning and experimentation, making it an excellent place to thrive as an engineer.

How has your role evolved since you started?
When I first joined, my focus was more hands-on-developing machine learning models and optimizing detection systems. Over time, I transitioned into a leadership role, where I’m now responsible for the broader vision of our ML-driven security solutions and how they integrate into the product.

A big part of my growth has been learning how to scale not just technology, but also teams and processes. I’ve had the opportunity to shape how we approach ML-driven security at Abnormal, from research and development to deployment and iteration. AI continues to be central to this evolution, as we explore more advanced deep learning techniques, natural language processing, and anomaly detection methods to stay ahead of cyber threats.

What’s a challenge you and your team have tackled that you’re particularly proud of?
One of the biggest challenges in email security is staying ahead of adversaries who are constantly evolving their tactics. Our team recently made significant improvements to our anomaly detection models, which required rethinking how we process and analyze vast amounts of email data efficiently.

This project involved deep collaboration between ML engineers, data scientists, and software engineers. We had to balance precision and recall while ensuring our models could adapt to emerging threats in real-time. Seeing the direct impact of our work-how we’re stopping sophisticated attacks that would otherwise bypass traditional defenses-makes it incredibly rewarding.

What makes Abnormal a great place for engineers who want to grow?
At Abnormal, engineers have the opportunity to work on high-impact problems that require deep technical expertise and creativity. The company encourages ownership, so if you see an area where we can improve, you have the autonomy to drive change.

We also have a strong culture of mentorship and learning. Whether it’s through technical deep dives, sharing best practices, or working on challenging problems together, there’s a continuous focus on growing as engineers and as leaders. Engineers are empowered to take risks, experiment with new ideas, and build solutions that have a real-world impact. It’s an incredibly rewarding place to be, and I’ve personally grown so much here, not only as an engineer but also as a leader.

Another thing that makes Abnormal stand out is the emphasis on work-life balance. In the tech industry, it’s easy to burn out, but here, leadership actively supports a culture where people can do great work without sacrificing their well-being. That’s something I really appreciate and something that makes me want to continue growing my career here.

What advice would you give to engineers considering a career at Abnormal?
If you love solving complex problems and want to work in a place where you can make a real impact, Abnormal is the place for you. Be curious, be willing to take on new challenges, and don’t be afraid to step outside your comfort zone.

One of the most important things I’ve learned is that growth happens when you take on responsibilities that stretch your abilities. If you’re eager to grow, there will always be opportunities here to lead, innovate, and make meaningful contributions. AI and machine learning are evolving rapidly, and we need engineers who are excited to push the boundaries of what’s possible.

The future of AI in security is incredibly exciting, and I truly believe we’re at the forefront of some of the most impactful innovations in this space. If that excites you, come join us.

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Angela’s journey at Abnormal is a testament to the power of leadership, innovation, and technical excellence. If you’re a curious engineer looking to experiment on cutting-edge machine learning challenges, check out our open roles.