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AI security · enterprise cybersecurity

(Sr.) Applied AI Engineer

TaiwanPosted 6 days ago
Machine learningSeniorFull Time
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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

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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