About the Role
At Inceptive, you will drive forward development that could help billions of people. To accomplish this, you will be part of a collaborative, antedisciplinary team building our biological software.
Our AI models depend on rich, high-quality biological datasets. The integrity, security, and reliability of those datasets and of the infrastructure that supports them are critical to everything we do. As we scale, we need someone who can architect and own the systems that keep our data and our customer's data safe, well-governed, and optimally accessible to our machine learning pipelines. This is a senior, hands-on role: you will design and build, not just advise.
You will work closely with our ML researchers, data engineers, and computational biologists to understand data flows end to end, including data ingestion, training, inference, analysis, logging, result output, and model serving.
Your Mission, Should You Choose to Accept It
- Architect, implement, and own secure data infrastructure supporting our AI model training and deployment pipelines
- Build and operate foundational security services: authentication systems, access brokers, secrets management, key management platforms, and egress/ingress controls across our multi-cloud environment
- Design and enforce data governance frameworks, such as RBAC/ABAC policies, audit logging, encryption at rest and in transit, workload identity, and data lifecycle management
- Embed security directly into our MLOps pipeline: CI/CD security controls, container and Kubernetes security, namespace isolation, and pod security standards
- Conduct threat modeling and secure design reviews for existing and new systems
- Identify, prioritize, and drive remediation of vulnerabilities across our data systems, cloud environments, and ML tooling, including AI-specific risks like data poisoning and model extraction
- Build detection and alerting pipelines for anomalous data access patterns and potential exfiltration events
- Establish security best practices and educate team members on secure coding and secure data handling for AI systems
Qualifications and Requirements
- 7+ years of hands-on experience in data engineering, infrastructure security, or software security
- 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
- Hands-on experience with Kubernetes security: RBAC policies, namespace isolation, workload identity, pod security
- Certifications highly desirable: CISSP, OSCP, GWAPT, GAISC, or Offensive ML (OffSec)
- Availability to work with team members across US and Europe
- We value the benefits of in-person collaboration and expect candidates to primarily work from our Palo Alto or Berlin offices
Preferred Technical Skills
- PhD or advanced degree in Computer Science, Electrical Engineering, or a related field
- Familiarity with AI/ML-specific security risks: data poisoning, model extraction, prompt injection, unauthorized model weight access
- 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
- Experience with compliance frameworks relevant to sensitive research data (SOC 2, HIPAA, GDPR)
- Background in offensive security techniques
Compensation
$200K - $275K + Bonus + Equity
What We Offer
- A competitive compensation package
- 30 days paid vacation per year
- Direktversicherung for German-based employees
- Quarterly company-wide retreats
- Monthly wellness benefit
- Budget for multiple visits per year to our offices in Berlin, Palo Alto or Switzerland
- Learning & Development budget