(Sr.) Applied AI Engineer
Trend Micro · Taipei
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趨勢科技 - 全球雲端資安領航者 / 全亞洲最大軟體公司 / 企業版圖橫跨五大洲 / 趨勢全球研發基地在台灣
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TrendAI is a global cybersecurity leader, protecting hundreds of thousands of organizations across clouds, networks, devices, and endpoints. Now we're building the most cutting-edge AI projects in security — and we need people who can turn them into products that matter.
We're hiring a (Sr.) Applied AI Engineer to work at the frontier: designing and shipping AI capabilities, agents, and infrastructure that reshape what our products can do. (Yes, we also use AI to build faster — AI-driven development is part of how we work, not the point of the job.)
This isn't a role for someone who just uses AI. We want someone who has changed a product or project with AI in production — or built something genuinely impressive on their own.
Your Mission
Build and ship frontier AI projects — agents, LLM-powered features, the things that move the product forward.
Design and operate the AI infrastructure behind them: agents, evaluation harnesses, telemetry, platform services.
Take ideas from pilot to real impact — own the outcome, prove it changed something.
Solve hard problems across the AI/agent stack, root cause to durable fix.
What We're Looking For
Proficiency in Python plus one more language (Golang, Java, C/C++).
A real story to tell: an AI project or capability you built or drove into a product — and can prove the impact. Or a substantial AI project you built end to end. Everyday tool use doesn't count.
Fast to POC: you can go from idea to working prototype quickly, and iterate from there.
Always on the frontier: you actively embrace the latest AI techniques and bring them into your work.
Hands-on with AI coding agents (Claude Code) — beyond casual prompting.
AI agent design and multi-agent systems.
Context engineering, harness engineering, skill/tool design for reliable LLM behavior.
Sharp judgment on LLM outputs — quality, correctness, hallucination, subtle failure modes.
Bonus
Agentic platform design.
Supervised fine-tuning (SFT) of language models.
NVIDIA tech stack (CUDA, NeMo, Triton, TensorRT, etc.).
AI token optimization at very large scale.
Driving AI-native development adoption across an engineering org.
Retrieval and memory layers around LLMs, with simplicity-first instinct.
Developer tools or AI infra at company scale.
Cloud (AWS / Azure / GCP), Docker/Kubernetes, IaC (Terraform).
You'll Fit If
You're genuinely excited about AI and love sharing what you learn.
You experiment, ship, and keep learning in a fast-moving space.
Strong proactive, a reliable teammate in cross-functional work.
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連結智慧 守護世界 --- Connected Intelligence for Securing a Connected World