Virtualization Engineer - Aion

Aion is the enterprise AI platform, a full-stack solution for building, fine-tuning, and deploying AI at scale. Whether an organization is modernizing internal operations, launching AI-powered products, or transforming customer experiences, Aion takes them from concept to production on a single, unified platform.

We work differently than most AI companies: our teams deploy alongside our customers, turning production-ready AI into real business outcomes in weeks, not quarters.

We’re a fast-growing, VC-backed startup led by founders with a track record of successful exits. With teams across the US, UK, and India, we’re building the next generation of enterprise AI and we’re looking for exceptional people to help us scale.

You're a systems engineer with deep expertise in virtualization, cloud infrastructure, and compute resource management. You understand how modern virtualization technologies power scalable, secure, and high-performance AI infrastructure across on-premises, hybrid, and cloud environments.

You have experience building virtualization platforms that maximize infrastructure efficiency while providing strong isolation, performance, and operational reliability. You're comfortable working across Linux systems, hypervisors, containers, Kubernetes, networking, and virtualization technologies.

You think beyond infrastructure. You understand how virtualization directly impacts AI model performance, developer productivity, platform scalability, and enterprise deployments. You're excited to solve complex systems problems while building the foundation that powers enterprise AI workloads.

You're a team player who enjoys working across infrastructure, platform engineering, product, and customer success teams to deliver production-ready virtualization solutions for customers globally.

Virtualization Platform & Infrastructure

• Design and build Aion's virtualization platform for running AI workloads across cloud, hybrid, and on-premises environments.
• Architect secure, scalable, and high-performance virtualization infrastructure supporting enterprise AI deployments.
• Build virtualization services that optimize compute utilization while maintaining workload isolation and reliability.
• Develop reusable platform components that simplify provisioning, lifecycle management, and infrastructure automation.

Compute & Resource Management

• Design intelligent compute scheduling and resource allocation strategies for CPU, memory, storage, networking, and GPU resources.
• Implement virtualization technologies that improve infrastructure utilization while ensuring predictable performance.
• Optimize workload placement, scaling, and resource balancing across distributed clusters.
• Build automation for provisioning, migration, recovery, and lifecycle management of virtualized environments.

Performance & Systems Engineering