Tech Stack
AWSAzureCloudDockerGraphQLKubernetesNeo4jNoSQLPostgresPythonRedisSQL
About the role
- Design and implement a comprehensive data privacy and access control architecture addressing multi-dimensional classification, dynamic permissions, and information barriers
- Build a custom encryption service within a micro-services architecture, including secure service development, OAuth integrations, and identity provider connections
- Architect a multi-layered access control model combining Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC), and purpose-based limitations
- Oversee implementation of fine-grained data classification frameworks using NLP and other technologies
- Design and validate permission propagation mechanisms for graph data models and derived insights
- Establish security boundaries for autonomous AI agents, ensuring proper context isolation and privilege controls
- Work closely with engineering teams to integrate privacy controls into the data pipeline, knowledge graph, and AI components
- Collaborate with product management to balance privacy requirements with usability and functionality
- Coordinate with customer success to address client-specific privacy and compliance needs
- Develop and enforce security and privacy standards, policies, and best practices throughout the product development lifecycle
- Influence and guide development teams to prioritize privacy-by-design principles
Requirements
- 5+ years of experience in information security, data privacy, or access control systems
- Proven track record designing and implementing complex security architectures
- Strong knowledge of modern authorization frameworks, RBAC/ABAC systems, and data classification methodologies
- Experience leading teams and influencing cross-functional stakeholders
- Technical background with understanding of databases, APIs, and enterprise software architecture
- Knowledge of AI/ML systems and the unique privacy challenges they present
- Understanding of data privacy regulations (GDPR, CCPA) and their technical implementation requirements
- Familiarity with LLMs and the privacy implications of their use in enterprise contexts
- Understanding of vector databases and embedding-based systems
- Experience in regulated industries (finance, healthcare, legal) with complex information barrier requirements
- Background in data lineage and provenance tracking systems
- Experience with graph databases (particularly Neo4j) and their security models
- Security certifications such as CISSP, CIPT, or CIPP/E
- Experience building encryption systems (e.g. AES, RSA, and key management services)
- Hands-on development with OAuth 2.0, OpenID Connect, JWT validation, and RBAC/ABAC systems
- Building secure REST/GraphQL APIs with middleware for authentication, rate limiting, and input validation
- Implementing access controls, query filtering, and audit logging for SQL and NoSQL databases
- Securing pub/sub systems with encryption, authentication, and access controls
- Required technologies: Python (async/await, cryptography libraries, FastAPI); Container security (Docker, Kubernetes secrets, network policies); Identity providers (Microsoft EntraID, Okta, Auth0 integration); Database systems (PostgreSQL, Redis, graph databases); Cloud security (AWS/Azure IAM, KMS, security groups)
- Practical experience: built production encryption/decryption systems handling sensitive data at scale; implemented fine-grained permission systems beyond simple role-based access; developed secure multi-tenant applications with data isolation; created audit logging and compliance reporting for regulated environments; integrated with enterprise identity systems in complex organizational structures