Sr. Software Engineer, Sandboxes & Virtualization
About this role
The Runtime & GPU Systems team builds and operates secure, high-performance environments for multi-tenant Kubernetes platforms at scale. Sitting at the intersection of container runtimes, lightweight virtualization, GPU infrastructure, and Linux systems engineering, the group collaborates with security, platform, and GPU infrastructure partners to deliver robust, isolated execution environments for AI-driven workloads.
Engineers joining this group design, build, and evolve secure sandboxed runtime environments for Kubernetes, concentrating heavily on runtime isolation, performance, and security. Daily responsibilities involve integrating container runtimes and lightweight VMs, developing GPU-aware scheduling strategies, and optimizing I/O performance for latency-sensitive operations. Ideal candidates possess a strong foundation in systems programming and Kubernetes, bringing practical experience with virtualization and a collaborative mindset suited for a fast-paced cloud environment.
What you will do
- Design and implement secure execution environments for both containerized and virtualized workloads.
- Build GPU-aware scheduling, isolation, and resource management strategies to support multi-tenant usage.
- Optimize container, virtual machine, and I/O performance across various GPU-accelerated workloads.
- Conduct profiling, benchmarking, and performance tuning for runtime, virtualization, and GPU technology stacks.
- Contribute to architectural decisions spanning Linux internals, container runtimes, virtualization layers, and GPU drivers.
- Collaborate directly with security, platform, and infrastructure teams to establish runtime isolation and performance standards.
What you need
- Bring at least 3 years of professional experience working in systems, platform, infrastructure, or production engineering at scale.
- Demonstrate strong hands-on experience with Kubernetes, container orchestration, and cloud-native architectures including controllers and operators.
- Show documented background in designing, implementing, or operating secure execution environments like sandboxed workloads and container runtimes.
- Possess practical familiarity with lightweight virtualization technologies such as Kata Containers, gVisor, KubeVirt, or QEMU.
- Have direct experience supporting GPU-accelerated workloads in multi-tenant environments through GPU scheduling, isolation, or device passthrough.
- Demonstrate proficiency in systems-oriented programming using Go alongside a solid understanding of Linux internals.
- Display skill in diagnosing and resolving complex performance, reliability, and isolation issues across containers, VMs, and underlying infrastructure.
Nice to have
- Experience building systems for safely executing untrusted or sensitive workloads in shared environments
- Familiarity with GPU drivers and low-level virtualization or I/O optimization techniques
- Experience defining threat models and implementing runtime security policies in multi-tenant systems
Benefits
- Medical, dental, and vision insurance - 100% paid for by CoreWeave
- Company-paid Life Insurance and voluntary supplemental life insurance
- Short and long-term disability insurance, Flexible Spending Account, and Health Savings Account
- Tuition Reimbursement and participation in Employee Stock Purchase Program
- Mental Wellness Benefits through Spring Health and family-forming support provided by Carrot
- Paid Parental Leave, childcare support with Kinside, and 401(k) with a generous employer match
Skills and tech stack
Questions candidates ask
What is the compensation range for this position?
The base salary range for this role is $153,000 to $204,000. The starting salary is determined based on job-related knowledge, skills, experience, and market location.
What technologies and systems will I be working with?
You will work with Kubernetes, container runtimes, lightweight virtualization technologies like Kata Containers and QEMU, Linux internals, and GPU-accelerated infrastructure. The role also requires systems-oriented programming using Go.
What team will I be joining?
You will join the Runtime & GPU Systems team, which builds and operates secure, high-performance environments for multi-tenant Kubernetes platforms at scale. The team partners closely with security, platform, and GPU infrastructure groups.