AI-native Tech Operations Lead - Remote

Sphere Technology; Manila; À distance; PHP 1 500 000 - 2 300 000; Plein temps

Résumé du poste

Sphere Technology is seeking an AI-native Technical Operations Lead based in the Philippines to own the operational backbone of an AI-driven platform. You will oversee development environments, CI/CD pipelines, and QA frameworks, enabling engineering leadership to focus on product delivery.

This is a remote role with a start-up mindset and a fast-moving roadmap. Ideal candidates have 3–7 years of full-stack engineering, strong QA discipline, and experience with AI-assisted tooling.

Qualifications

• 3-7 years of engineering experience across the full stack.
• Strong QA and testing discipline—meticulous, not just functional.
• Comfort working across multiple languages and frameworks.
• DevOps experience including CI/CD and Docker.

Responsabilités

• Prepare development environments, run test suites, and stage context ahead of engineering sessions.
• Review and test all code produced during engineering sessions - regression testing and bug documentation.
• Manage CI/CD pipelines, staging and production deployments, and infrastructure monitoring.
• Handle lower-complexity coding tasks independently using AI-assisted workflows (30-40% of role).
• Build out tests, fix non-critical bugs, implement UI refinements, and create utility scripts.
• Research and prototype third-party API integrations (healthcare, payments, scheduling).
• Maintain technical documentation current with each sprint and support regulatory compliance requirements.

Outils

Docker

CI/CD

Cloud infrastructure

Description du poste

Sphere Technology is seeking an AI-native Technical Operations Lead based in the Philippines to own the operational backbone of an AI-driven platform. You will oversee development environments, CI/CD pipelines, and QA frameworks, enabling engineering leadership to focus on product delivery.

This is a remote role with a start-up mindset and a fast-moving roadmap. Ideal candidates have 3–7 years of full-stack engineering, strong QA discipline, and experience with AI-assisted tooling.