Member of Technical Staff — Security Engineering
Causal · San Francisco
About this role
## Member of Technical Staff — Security Engineering ### About the role At Causal Labs, we’re building a **Large Physics Model (LPM)** to enable AI that can **predict the future** and **identify actions to alter it**. As we scale our research and deploy high-stakes systems, we need security that protects our engineering stack end-to-end—without slowing down iteration. You’ll design and operate the **security posture across our entire engineering stack**, ensuring our research environments, proprietary model weights, infrastructure, and customer integrations remain secure. ### Responsibilities - **Enterprise Infrastructure & Cloud Isolation** - Architect secure network perimeters and private data transmission channels (e.g., **PrivateLink**, **VPNs**) - Build isolated single/multi-tenant storage environments - Implement access controls and **customer-managed encryption** (KMS/BYOK) for petabyte-scale data stores - **Model IP & Weight Protection** - Create **zero-trust** boundaries - Use encrypted storage and secure execution environments to protect proprietary model weights/checkpoints - Defend against exfiltration during storage, distributed training, and serving - **Pipeline Integrity & AI Threat Defense** - Secure data ingestion pipelines against tampering and **data poisoning** - Threat-model and defend against AI-specific vulnerabilities, including: - adversarial inputs - model extraction attacks - data memorization/regurgitation risks - Apply output guardrails and privacy-preserving techniques - **Enterprise Auth & Governance** - Own enterprise identity federation (**SAML 2.0 / OIDC** with Okta, Entra ID) - Implement machine-to-machine authentication (**mTLS**) - Deliver immutable audit logging, cryptographic erasure, and compliance controls for **SOC 2 / FedRAMP**-style environments - **Security Engineering & SDLC** - Partner with Infrastructure, Research, and Forward Deployed teams to embed: - automated security testing - threat detection - vulnerability scanning - Integrate directly into deployment workflows, orchestrators (**Kubernetes, Slurm**), and customer-facing APIs ### What we’re looking for - **Hands-on Security Engineering** - Proven track record securing production systems in cloud (AWS/GCP/Azure) or large distributed environments - Strong command of core primitives: **IAM, network perimeters, KMS/encryption, secrets management** - **Systems & Software Background** - Hands-on **Linux**, networking, and container security (Docker/Kubernetes) - Infrastructure-as-Code (**Terraform** or **Pulumi**) - Proficiency in **Python, Go, or Rust** - **ML Platform Security Understanding** - Practical experience securing ML platforms: protecting model weights, distributed training pipelines, data lineage/poisoning, and AI threat vectors - **Adaptable & High Agency** - Ability to run architectural security reviews and dive into complex distributed systems - Comfort adapting quickly to new constraints and bespoke enterprise environments - **Bias Toward Real-World Impact** - Pragmatic delivery that works under pressure—balancing rigor with engineering velocity - **End-to-End Ownership** - Take security deliverables from threat modeling and requirements through execution, deployment, and monitoring
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