Fullstack Engineer - AgenticOps (100% Remote)

About the role

Tether is looking for a Fullstack Engineer to help its QVAC application teams develop, review, test and deliver reliable software with less friction. The focus is on desktop and mobile applications and their shared runtime, AI harness and skills packages. You will build and maintain developer tools, integrate AI agents into engineering workflows and improve code quality and delivery automation. This is a hands-on engineering role with room to shape the tooling roadmap, working with engineers to own improvements from implementation through adoption and ongoing support.

Key responsibilities

• Evaluate, integrate and maintain developer tools and AI agents, including the repository guidance and integrations they need.
• Build and operate agents in CI and scheduled workflows that investigate failures, propose fixes and give engineers evidence they can act on.
• Improve automated pull request reviews, evaluating finding accuracy and reducing noise for reviewers.
• Develop code quality scripts and checks for complexity, function and file size, dependency cycles and performance regressions, working with package owners on thresholds and refactoring.
• Improve development environments, testing and build and release workflows so engineers and agents can verify changes reliably.
• Prioritize improvements with engineering teams, support adoption through documentation and onboarding, and measure effectiveness, reliability and operating costs.

Required profile

• Experience building and maintaining developer tools or engineering automation used by others.
• Hands-on experience using and integrating AI coding tools or agents, with sound judgment about their limitations, output validation and human review.
• Ability to work independently, collaborate with engineers and communicate clearly in English within a remote, globally distributed team.

Required skills

• Strong JavaScript/TypeScript and Node.js skills.
• Git, CI/CD, automated testing and systematic debugging of build, test or integration failures.
• A strong approach to code quality: maintainable code, useful automated checks and refactoring that preserves behavior.