Infrastructure Engineer, Security (AI)

TL;DR

Infrastructure Engineer, Security (AI): Own and evolve the security infrastructure underpinning foundation models with an accent on architecting secure patterns for platforms and services, and managing identity, access, and secrets. Focus on building secure data platforms, writing threat models, and automating security checks in Kubernetes and cloud environments.

Location: This role is based in San Francisco, California. Visa sponsorship is available, and relocation support is provided as needed.

Salary: $200,000 – $475,000 USD annually

Company

hirify.global is a company building advanced collaborative general intelligence, with founders having created widely used AI products and open-source projects.

What you will do

• Architect security patterns for platforms and services, including network segmentation and authentication in Kubernetes and cloud environments.
• Manage identity, access, and secrets for humans and services across workload and cross-cloud environments.
• Build secure platforms for data ingestion, processing, and curation with classification, encryption, and access controls.
• Write threat models and review designs with researchers and engineers to help ship features and experiments safely.
• Automate security checks and build guardrails using policy-as-code and secure infrastructure baselines in CI/CD.

Requirements

• Bachelor’s degree or equivalent experience in engineering.
• Strong background with containers and orchestration (e.g., Kubernetes) and securing them.
• Practical experience with Infrastructure as Code (e.g., Terraform) for provisioning secure networks and IAM.
• Solid understanding of cloud networking and security, including VPCs, load balancers, and zero-trust-style architectures.
• Proficiency with a systems language such as Rust and scripting in Python for building platform components and internal tools.
• Evidence of owning complex, production-critical systems, including debugging issues across infra, security, and application layers.

Nice to have

• Experience with ML infrastructure, GPU clusters, or large-scale training environments.
• Background in AI labs, HPC environments, or ML-heavy organizations where security and performance are critical.
• Experience profiling and tuning high-throughput systems, and an ability to reason about the cost of additional security layers.
• Contributions to open-source in security, orchestration, observability, or infrastructure tooling.
• Familiarity with securing specialized hardware (GPUs, TPUs) and their integrations into training and inference pipelines.

Culture & Benefits

• Generous health, dental, and vision benefits.
• Unlimited PTO and paid parental leave.
• Relocation support as needed.
• Work with a team of scientists, engineers, and builders who have created widely used AI products and open-source projects.