Software Engineer – Platform Security
Required skills
- Kubernetes
- serverless
- multi-tenant
- container isolation
- control plane
- data plane
- guardrails as code
- Terraform
- Helm
- network segmentation
Nice to have
- Knative
- container hardening
- sandboxing
- policy-as-code
- admission policy
- eBPF
Role summary
FriendliAI is seeking a Software Engineer for Platform Security to architect and build security foundations for their multi-tenant serverless compute platform on Kubernetes. This hands-on role involves owning security design for control and data planes, implementing guardrails as code using Terraform and Helm, and establishing network segmentation, secrets management, and runtime detections. The ideal candidate has 5+ years of experience securing cloud-native platforms, strong AWS and Kubernetes security expertise, and proficiency in IaC tools. Preferred experience includes serverless frameworks, container hardening, policy-as-code, eBPF, and compliance automation.
About the job
FriendliAI is looking for an engineer to architect and build the security foundations of a multi-tenant serverless compute platform running on Kubernetes with hardened container isolation. As a Software Engineer, Platform Security, you will own the security design for both the control plane and data plane, implement guardrails as code, and partner closely with Platform/SRE/Infra teams to ship a secure-by-default developer experience. This is a hands-on builder and architect role.
Key Responsibilities
Design and implement the security architecture for a Kubernetes-based, multi-tenant serverless platform.
Build guardrails as code using Terraform and Helm.
Establish network segmentation and service-mesh policy.
Develop secrets and key management patterns.
Implement runtime detections for containerized workloads.
Design and roll out IAM & workload identity management.
Threat model new features and changes to the overall platform.
Collaborate with engineering to debug production issues, lead post-incident hardening, and automate evidence for compliance controls.
Qualifications
5+ years securing cloud-native platforms with a focus on distributed systems and multi-tenancy.
Bachelor’s or Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent.
Strong hands-on experience with AWS (IAM, VPC/networking, logging/monitoring, …) and Kubernetes/container security.
Proficiency with Terraform and Helm.
Experience building or operating runtime detections for containers/functions.
Strong technical background in backend systems, cloud infrastructure, or AI tooling
Clear written and verbal communication; ability to translate pricing/business rules into robust systems.
Preferred Experience
Knative or similar serverless-on-K8s frameworks.
Container hardening and sandboxing.
Policy-as-code and admission policy design at scale.
eBPF-based observability, detections, and signal tuning.
Multi-cloud exposure and cross-cloud identity approaches.
Hands-on contributions to SOC 2 / HIPAA control automation and audit evidence pipelines.
Benefits
A front-row seat to the generative AI infrastructure revolution
Competitive compensation and benefits package
Daily lunch and dinner provided; unlimited snacks and beverages
Health check-up and top-tier hardware support
Flexible working hours and a highly collaborative environment
About us
FriendliAI is building the next-generation AI inference platform that accelerates the deployment of large language and multimodal models with unmatched performance and efficiency. Our infrastructure powers high-throughput, low-latency workloads for global organizations and integrates directly with Hugging Face, providing instant access to over 600,000 open-source models. We are on a mission to deliver the world’s best platform for AI inference.
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