AI Infrastructure Operations Engineer
Company: Private Health Management
Location: Location not specified (Remote)
Type: Full-time
Remote: Yes
Posted: 2026-06-06
About this role
AI Infrastructure & Operations Engineer
Location:
Remote (U.S.)
Reports To:
Juan Sandoval-Tobias
About Private Health Management
Private Health Management (PHM) supports people with serious and complex medical conditions, helping them obtain the best possible medical care. We guide individuals and families to top specialists, advanced diagnostics, and personalized care. Trusted by healthcare providers and businesses, PHM offers independent, science-backed insights to help clients make informed decisions and access the best care.
About the Role
PHM is building and scaling Companion, an AI-enabled clinical platform operating in a high-trust healthcare environment where reliability, observability, and security are foundational requirements. The platform includes headless AI agents designed to support clinical and operational professionals by acting as intelligent workstations that integrate with enterprise applications and workflows.
The AI Infrastructure & Operations Engineer will operationalize the platform so it runs reliably at production scale, helping ensure the systems behind Companion are observable, recoverable, secure, and maintainable as adoption grows.
This role sits at the intersection of Kubernetes operations, AI platform reliability, observability engineering, and operational security. You will help evolve and maintain the Azure-based infrastructure stack while partnering closely with technology leadership, AI architects, and security stakeholders. This is a high-ownership role for someone who thrives in fast-moving environments, is comfortable operating with incomplete information, and enjoys building operational discipline around emerging AI systems.
What You’ll Accomplish
- Establish operational reliability for Companion across AKS infrastructure, AI agent workloads, monitoring systems, and deployment pipelines.
- Build meaningful observability practices that help PHM understand platform beh...