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Friendliai

Software Engineer – Platform Security

  • Seen live on Friendliai's site 3 days ago
  • Mid level
Pay
Not stated
Location
Seoul
Open for
11+ days
First seen
Oct 24, 2026
Apply on Friendliai's site (opens in a new tab)

Posting record

No flags

Open 11+ days

The posting's record, oldest first
  1. Friendliai's site dates the posting
  2. Ghostless first sees this listing
  3. Last checked: still up
How we know

It hasn't been reposted, listed twice, or left up unusually long, and the posting doesn't say it's a talent pool.

Ghostless records the day it first sees a posting, so a repost can't reset its age. This one was already up when Ghostless started tracking Friendliai, so its true age is longer.

Last checked Nov 1, 2026.

How well do you match?

See how much of this posting your resume shows, and what it's missing.

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What it asks of you

Master's degree asked for
“Bachelor’s or Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent.” (quoted from the posting)

What the posting discloses

Not stated: Pay, real vacancy, AI screening.

Why these three

Ontario requires postings from employers with 25 or more staff to state the pay, whether the vacancy exists, and whether AI screens applicants.

Some employers add pay only on their own site. Check the original posting before you rule it out.

Skills mentioned

About the role

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 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

  • Flexible working hours
  • Daily lunch and dinner provided; unlimited snacks and beverages
  • Supportive and highly collaborative work environment
  • Health check-up support and top-tier equipment/hardware support
  • A front-row seat to the generative AI infrastructure revolution
  • Competitive compensation, startup equity, health insurance, and other benefits.

About FriendliAI

FriendliAI is building the world’s best AI inference platform that makes large language and multi-modal models fast, efficient, and deployable at scale. We power high-throughput, low-latency AI workloads for organizations worldwide and integrate directly with Hugging Face, giving developers instant access to over 600,000 open-source models.

We are a small, fast-moving team doing work that matters at one of the most exciting moments in the history of technology. With our world-class inference engine, we are building a platform that the AI industry can actually rely on.

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