Senior Secure Data Infrastructure Engineer for AI

About the role

Inceptive is looking for a senior engineer to design, build, and own the secure data infrastructure that powers its AI models. You will work in a highly interdisciplinary team that blends biology, machine learning, and software engineering to protect critical research data and model assets.

Key responsibilities

• Architect and operate secure data pipelines from raw ingestion to model weight storage across a multi‑cloud environment.
• Build foundational security services such as authentication, secrets management, key management, and egress/ingress controls.
• Define and enforce data governance frameworks, including RBAC/ABAC policies, audit logging, encryption at rest and in transit, and data lifecycle management.
• Integrate security into MLOps: CI/CD security checks, container and Kubernetes hardening, namespace isolation, and pod security standards.
• Conduct threat modeling, secure design reviews, and vulnerability remediation for data systems, cloud platforms, and ML tooling.
• Develop detection and alerting pipelines for anomalous data access and potential exfiltration.
• Educate team members on secure coding, infrastructure patterns, and best practices for handling sensitive AI data.

Required profile

• 7+ years of hands‑on experience in data engineering, infrastructure security, or software security.
• Proven ability to design and operate large‑scale, secure data platforms in a multi‑cloud setting.
• Experience collaborating with ML researchers, data engineers, and domain scientists.
• Strong analytical mindset with a focus on proactive risk mitigation.

Required skills

• Kubernetes security and container hardening
• CI/CD security controls
• Authentication and access‑control systems (RBAC/ABAC)
• Secrets and key management platforms
• Encryption at rest and in transit
• Audit logging and data lifecycle management
• Threat modeling and secure design reviews
• Vulnerability assessment and remediation
• Multi‑cloud environment management