AI Infrastructure Engineer

Design, build, and evolve secure, scalable cloud infrastructure for real-time AI services and customer-facing applications.

Improve service reliability through clear SLOs, actionable observability, capacity planning, failure testing, and pragmatic incident prevention.

Build deployment and release systems that make production changes fast, repeatable, auditable, and safe.

Own infrastructure as code, environment consistency, and reusable platform patterns across development, staging, and production.

Partner with product and AI engineers on architecture, performance, data flows, and operational readiness for new capabilities.

Diagnose complex distributed-system failures across application, network, database, model-provider, and third-party integration boundaries.

Reduce infrastructure and model-serving cost without compromising customer experience or engineering velocity.

Strengthen secrets management, access controls, backup and recovery, vulnerability management, and other practical security foundations.

Build internal tooling and paved paths that let engineers ship and operate services with less manual work.

Participate in incident response and turn incidents into better systems, automation, documentation, and engineering judgment.