7+ years of hands-on experience in data engineering, infrastructure security, or software security, ideally spanning both disciplines
Strong System and Software Engineering skills with production-quality code in Python, Bash, and at least one systems programming language (Go, Rust, or C++)
Deep experience securing GCP cloud environments, including IAM, VPC design, secrets management, workload authentication, and cloud security posture management
Proven track record designing and implementing identity and access management systems, including credential issuance, rotation, and least-privilege enforcement at scale
Hands-on experience with Kubernetes security: RBAC policies, namespace isolation, workload identity, pod security
Certifications (Highly Desirable): CISSP, OSCP, or GWAPT for core security credentialing, plus AI-focused certifications such as GAISC, Offensive ML (OffSec), or cloud provider AI security tracks (AWS/GCP).
Availability to work with team members across US and Europe, with meetings starting at 8am PT and ending at 7pm CET
Readiness to travel several times a year for company retreats and business events
We value the benefits of in-person collaboration and expect candidates to primarily work from our Palo Alto or Berlin offices
PhD or advanced degree in Computer Science, Electrical Engineering, or a related field or equivalent practical experience
Familiarity with AI/ML-specific security risks: data poisoning, model extraction, prompt injection, unauthorized model weight access, and adversarial attacks on training pipelines, and practical mitigations for each
Experience securing ML infrastructure, including model registries, training cluster access, dataset versioning, experiment tracking systems, and GPU compute environments
Proficiency with Terraform infrastructure-as-code and GitOps security practices, including automated misconfiguration detection and remediation
Experience with compliance frameworks relevant to sensitive research data (SOC 2, HIPAA, GDPR) and translating them into concrete engineering controls
Background in offensive security techniques, including threat modeling, penetration testing, vulnerability research, or red team exercises. In a nutshell, the ability to think like an adversary
Experience building detection pipelines for insider threats, data exfiltration, and anomalous access patterns
Knowledge of cryptographic protocols and their practical application in distributed systems (key management, TLS, secure enclaves)
Prior experience in a fast-moving startup or research environment where security must scale alongside rapid growth

Secure data infrastructure for AI

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