Infrastructure Engineer (AI Security)

Location: On-site in San Francisco, California, United States

Annual salary: $300,000–$350,000 USD

Company

Thinking Machines Lab builds AI that extends human will and judgment, including frontier models with Inkling, customizable model infrastructure with Tinker, and interfaces for human-AI communication.

What you will do

• Architect security patterns for platforms and services, including network segmentation, service-to-service authentication, RBAC, and policy enforcement in Kubernetes and cloud environments.
• Manage human and service identity, access, workload and cross-cloud identity, least-privilege IAM, and secrets management.
• Build secure platforms for data ingestion, processing, and curation with classification, encryption, access controls, and safe cross-team sharing.
• Write threat models and review designs with researchers and engineers to support safe, scalable feature and experiment delivery.
• Automate security checks and build policy-as-code guardrails, secure infrastructure baselines, CI/CD validation, and secure-by-default tooling.

Requirements

• Bachelor’s degree or equivalent experience in engineering or a similar field.
• Strong experience with containers and orchestration, especially Kubernetes, including namespaces, network policies, pod security, and admission controls.
• Practical Infrastructure as Code experience with Terraform or similar tools, including secure provisioning patterns for networks, IAM, and shared services.
• Solid understanding of cloud networking and security, including VPCs, load balancers, service discovery, mTLS, firewalls, and zero-trust-style architectures.
• Proficiency in a systems language such as Rust and in Python scripting for platform components and internal tools.
• Evidence of owning complex, production-critical systems and debugging issues across infrastructure, security, and application layers.

Nice to have

• Experience with ML infrastructure, GPU clusters, or large-scale training environments, including schedulers, job queues, shared storage, and multi-tenant clusters.
• Experience in AI labs, HPC environments, or ML-focused organizations where security and performance are both first-class concerns.
• Experience profiling and tuning high-throughput systems and evaluating the cost of additional security layers.
• Talks, blogs, or publications on infrastructure security, distributed systems, or performance engineering.
• Open-source contributions to security, orchestration, observability, or infrastructure tooling.
• Familiarity with securing specialized hardware such as GPUs and TPUs and integrating it into training and inference pipelines.

Culture & Benefits

• On-site work in San Francisco, California.
• Health, dental, and vision benefits.
• Unlimited paid time off and paid parental leave.
• Relocation support as needed.
• Visa sponsorship is available, with support through the visa process for suitable candidates.