(Sr.) Applied AI Engineer (TrendLife)

AI is at the forefront of technological advancement — and cybersecurity is one of the fields being transformed the most. As a global cybersecurity leader with decades of threat research and intelligence, Trend Micro is committed to staying at the cutting edge of this shift, integrating AI to make the exchange of digital information safer and more secure for hundreds of thousands of organizations and millions of individuals worldwide.

TrendLife is our consumer-focused division, delivering the best security, privacy, and anti-scam solutions for everyday users. We build products that protect real people from real threats — phishing, identity fraud, malicious content, and more — and we do it by combining deep security expertise with fast, iterative product development.

AI is changing how software gets built — and we want engineers who are already living that change, not waiting for it. In a domain as fast-moving as consumer security and anti-scam, the ability to learn quickly, adapt, and validate ideas through real prototypes is more valuable than a perfect resume. This role is for someone who uses AI to move faster, thinks beyond the obvious solution, and is comfortable making real things under ambiguity.

The scope of this role spans both ends of the spectrum: building new products and services from the ground up, and rethinking or modifying the architecture of existing ones. Both happen here, and you will need to be comfortable with both.

Whether you are fresh out of school or a few years in, what matters most is your mindset: curiosity about how things work at a fundamental level, the habit of building to learn, and genuine enthusiasm for what AI makes possible.

AI-augmented development

You actively use AI tools to accelerate your own development work — not just for code completion, but to tackle harder problems faster, explore unfamiliar domains, and deliver more in less time. This applies across product development, service delivery, and internal tooling. We are not prescriptive about language — C, C++, Java, Python, Go, or anything else. What matters is whether you can leverage AI to pick up what is needed, move fast, and deliver working software. If you can build a convincing PoC in an unfamiliar language because you know how to work effectively with AI, that is exactly the point.

e.g. Using an LLM to rapidly prototype a scam-detection classifier, then iterating with real user feedback — rather than waiting for a complete spec before writing any code.

Curiosity about how things actually work

You are not satisfied with "it works" — you want to know why. When you hit a problem, you dig into the underlying mechanism rather than just patching the surface. In the security domain especially, this matters: understanding why a threat evades detection, or why a model behaves unexpectedly, is often the difference between a real fix and a temporary workaround.

e.g. Investigating why an anti-phishing model produces false positives on certain URL patterns — tracing it back to training data distribution rather than just adjusting thresholds.

Comfort with ambiguity and change

The AI and threat landscape moves faster than any roadmap can anticipate. You do not need a fully defined spec to get started. You can take a vague problem, make some reasonable assumptions, build a quick prototype, and use the result to sharpen the question. New attack vectors, shifting user behaviors, and evolving AI capabilities are not disruptions to you — they are the environment you work in.

e.g. When a new type of voice-cloning scam emerges, jumping in to explore detection approaches before the full product requirement is written.

POC-first work habit

Your instinct when facing an unknown is to build something small and learn from it — not to plan endlessly or wait for certainty. You are comfortable working in rapid cycles: rough prototype, real feedback, next iteration. This startup-style cadence feels natural to you, and you have a track record (even from side projects or academic work) of shipping things quickly to validate ideas.

e.g. Spinning up a lightweight demo of an AI-powered privacy scanner in a few days to pressure-test assumptions with the team — before committing to a full implementation plan.

Follows new tech

Keeps up with developments in AI and adjacent fields — not just passively, but with enough judgment to separate signal from noise. Can spot which emerging capability (e.g. multimodal models, on-device AI) might be relevant to consumer security before it becomes obvious.

Business awareness

Has some sense of how a product creates value and why certain technical choices matter commercially. Can connect an engineering decision to a real-world outcome — for example, understanding why latency in a real-time scam alert matters to user trust, not just to performance benchmarks.

A perfect resume. We care far more about how you think and how you work than where you went to school or how many years of experience you have. If you have built things, learned things, and can show us how you approach problems — that is what matters.

Deep ML research expertise, prior cybersecurity experience, or a background in large enterprise engineering are not requirements for this role.

ORG CONTEXT

This role is open to a range of experience levels — from recent graduates with strong fundamentals and genuine AI curiosity, to engineers with a few years of experience who have already developed this AI-first instinct. Level and compensation will be calibrated to your background. Everyone at TrendLife has the opportunity to contribute to real results for our customers — from day one.