Secure data infrastructure for AI

About This Opportunity

We are representing a confidential biotech organization at the forefront of AI-driven research. Our client is seeking a senior security engineer to architect and implement secure data infrastructure that protects their machine learning pipelines, training datasets, model weights, and experimental results. This is a hands-on role based in Berlin where you will own the systems that keep sensitive research data safe and optimally accessible.

You will collaborate with ML researchers, data engineers, and computational scientists to secure data flows from ingestion through training, inference, and model serving. Your work will protect critical assets from external threats and insider risks across multi-cloud environments.

Responsibilities

• Architect, implement, and own secure data infrastructure supporting AI model training and deployment pipelines from raw data ingestion to model weight storage
• Build and operate foundational security services including authentication systems, access brokers, secrets management, key management platforms, and egress/ingress controls
• 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 into MLOps pipelines with 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, identifying attack surfaces across the AI tech stack
• Drive remediation of vulnerabilities across data systems, cloud environments, and ML tooling, including AI-specific risks like data poisoning, model extraction, and unauthorized access
• 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, infrastructure patterns, and secure data handling for AI systems
• Partner with ML and research teams to ensure data handling practices meet the highest standards for sensitive research data

What We're Looking For

Required:

• 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 with credential issuance, rotation, and least-privilege enforcement at scale
• Hands-on experience with Kubernetes security: RBAC policies, namespace isolation, workload identity, pod security
• 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 per year for company retreats and business events
• Expectation to work primarily from the Berlin office

Preferred:

• Security certifications such as CISSP, OSCP, or GWAPT, plus AI-focused certifications like GAISC or cloud provider AI security tracks
• PhD or advanced degree in Computer Science, Electrical Engineering, or related field
• Familiarity with AI/ML-specific security risks including data poisoning, model extraction, prompt injection, and adversarial attacks on training pipelines
• Experience securing ML infrastructure including model registries, training cluster access, dataset versioning, 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 including threat modeling, penetration testing, vulnerability research, or red team exercises
• Experience building detection pipelines for insider threats, data exfiltration, and anomalous access patterns
• Knowledge of cryptographic protocols and their practical application in distributed systems
• Prior experience in a fast-moving startup or research environment

How We Work With You

When you apply through Get A Job.ai, one of our experienced recruiters will review your profile and conduct an initial screening call to understand your background and career goals. If there's a strong match, we will submit your candidacy to our client for consideration. We handle the coordination and serve as your advocate throughout the interview process.

Please apply exclusively through Get A Job.ai. Do not attempt to contact the client directly, as this may disqualify your application.

Pay

Compensation details will be discussed during the screening process with our recruiting team.

Get A Job.ai is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all candidates regardless of race, color, religion, sex, sexual orientation, gender identity, age, disability, marital status, citizenship, national origin, genetic information, or any other characteristic protected by law.