Junior Technical QA Associate — Architecture / Engineering Background
About the role
As a Junior Technical QA Associate, you will support project delivery by reviewing, tagging, labeling, validating, and organizing technical information related to construction drawings, 3D models, and AI-assisted workflows. You will work closely with team leads, QA specialists, and project delivery teams to ensure that the work we deliver is accurate, consistent, and useful to our customers from day one. This role is ideal for a recent graduate who wants to start their career in a modern, international, technology-driven environment.
What you'll do
- Review and interpret 2D construction drawings.
- Navigate and understand 3D models.
- Perform AI tagging, labeling, data validation, and quality assurance tasks.
- Check project information for accuracy, completeness, and consistency.
- Follow structured workflows and quality guidelines.
- Help identify errors, inconsistencies, or missing information.
- Collaborate with team leads and other remote team members.
- Learn new tools, processes, and project requirements quickly.
- Support continuous improvement by giving feedback on processes and workflows.
Requirements
- You have a Bachelor’s or Master’s degree in Architecture, Civil Engineering, or Mechanical Engineering.
- You have a good understanding of reading 2D construction drawings.
- You are comfortable learning how to navigate 3D models.
- You have strong English communication skills.
- You are detail-oriented and take pride in accurate work.
- You are adaptable, responsible, and have a strong work ethic.
- You are comfortable working remotely.
- You want your skills, effort, and contributions to drive your growth.
- You are excited to work with AI-assisted tools and modern digital workflows.
About Oliant
Oliant provides distributed QA operations for AI and SaaS companies through globally coordinated teams spanning the United States, Europe, and APAC. Their Philippines team serves as the APAC hub, supporting AI validation and testing for computer-vision platforms and AI-powered workflows.
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