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(Sr.) Applied AI Engineer

Trend Micro (UK) · Taipei

Full-timeOn-sitePosted 15 June 2026
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Job description

Join Trend ‧ Join New Generation 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 =============================================================== 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. =============================================================== 連結智慧 守護世界 --- Connected Intelligence for Securing a Connected World

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