(Sr.) Applied AI Engineer

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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