(Sr.) Applied AI DevOps Engineer
- Compensation
- Not disclosed
- Location
- Taipei
- Work setup
- Not specified
- Seniority
- Senior
- Employment
- Not specified
- Experience
- Not specified
- Category
- Ai engineering
- Posted
Skills
Must have
- Familiarity with AI-native development tools (e.g., Claude Code, GitHub Copilot, Cursor) and maintaining consistent AI configurations.
- Established a repeatable AI-native development workflow across every stage of the development lifecycle.
- Familiarity with context engineering practices and leveraging or building agent tools (e.g., AI Agent Skills, MCP servers).
- At least two years of experience designing and implementing software with high-level languages including Java / Python / bash script
- At least two years of experience in cloud computing with a preference to AWS, Azure, or GCP Hands on experience of infrastructure, systems and application architecture in large scale, web-based applic
- Experience in developing infrastructure as code including technologies like Terraform and Serverless
- Experience in container solution (e.g., Docker/K8S)
- Experience with testing and managing high availability environments with execution of disaster recovery tests on a regular basis
- Familiar with various cloud monitoring tools, performance monitoring and profiling tools
- Understanding of load testing, monitoring and performance management tools for every layer of the environment Strong customer service & customer focus with the ability to provide service to all levels
- Experience with at least one of CI/CD tools (e.g., Gitlab, Jenkins, GitHub Action etc).
Full description
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AI is currently at the forefront of technological advancement, marking a transformative shift across industries. As a global cybersecurity leader, Trend Micro is committed to staying at the cutting edge of this evolution, with the goal of integrating AI technology to make the exchange of digital information safer and more secure. Fueled by decades of security expertise, world-leading global threat research and intelligence, and continuous innovation, our cybersecurity platform protects hundreds of thousands of organizations and millions of individuals across clouds, networks, devices, and endpoints.
The objective of TW Engineering Group 1 is to deliver the best endpoint security solutions that help commercial customers face cybersecurity challenges effectively. We are dedicated to protecting businesses of all sizes—from small and medium-sized companies to large enterprises—so they can operate securely and confidently in today’s digital world. By harnessing the power of AI, we aim to create innovative solutions that solve real-world problems and keep all of our customers safe.
Everyone in Group 1 has the opportunity to join different teams and share their knowledge and passion, contributing to real results for our customers. Along this journey, we look for people who not only bring strong technical skills but also a forward-thinking mindset—those who can leverage AI technology to challenge the status quo, enhance productivity, and build innovative solutions that truly make a difference. We believe in adopting AI-powered development workflows to help our engineers produce more reliable, and high-quality programs, and create scalable products faster. This helps us learn from our customers and build solutions that truly make a difference.
As a (Sr.) DevOps Engineer, you will be responsible for building and maintaining robust backend services — contributing to CI/CD workflows, infrastructure-as-code, and DevSecOps practices across the software development lifecycle. You will also implement and maintain monitoring systems for product and service health checks, and join on-call rotations to triage and resolve customer-reported issues and service incidents.
Your Mission
- Leverage AI-native development tools (e.g., Claude Code, GitHub Copilot, Cursor) across every stage of the development lifecycle to deliver stable, high-quality output efficiently.
- Identify toil, design and implement automation within the SaaS
- Ensure the service performance, availability and reliability of all servers, services and microservices within the SaaS; maintain a high SLA.
- Provide operational support and automation tools to application developers including deployments to staging and production environments