We're seeking an experienced Security Developer to implement 's proprietary Genomic Veil (SGV) and Veiled Insights Framework (VIF) system for secure genomic data encryption and analysis. The ideal candidate will have 5-7 years of experience in security engineering with specific expertise in cryptographic implementations, distributed systems, and healthcare data privacy.
Key Responsibilities
Develop and implement proprietary SGV architecture
Build the cryptographic framework using AES-256 in GCM mode for securing genomic data
Implement the key management system with master key encryption and secret splitting across AI agents
Create the Veiled Insights Framework (VIF) that enables secure querying of encrypted twins
Design and develop Gene Parser and Digital Twin Generator modules including GAN integration
Establish secure storage for the distributed encrypted twins
Develop protocols for secure aggregation of insights without full genome reconstruction
Ensure all implementations are fully HIPAA-compliant and protect PHI according to regulations
Conduct regular security assessments and create documentation for HIPAA compliance audits
Collaborate with genomic researchers and data scientists to optimize the system for research usability
Required Skills & Experience
5-7 years as a security developer with focus on cryptographic implementations
Strong experience with AES-256 encryption, particularly in GCM mode
Demonstrated experience implementing HIPAA-compliant security systems
Thorough understanding of Protected Health Information (PHI) requirements and safeguards
Experience with building AI agents in healthcare data security and privacy regulations beyond HIPAA
Experience implementing key management systems and secret sharing algorithms
Proficiency in secure coding practices and identifying security vulnerabilities
Experience with distributed systems and secure multi-party computation
Strong programming skills in Python, Java, or C++
Experience with cloud security and securing data in distributed environments
Preferred Qualifications
Experience with Generative Adversarial Networks (GANs) or similar ML technologies
Background in homomorphic encryption or secure multi-party computation
Knowledge of differential privacy techniques
Experience building security systems specifically for genomic data
Proven track record of implementing systems that meet or exceed HIPAA Security Rule requirements
Experience conducting HIPAA security risk assessments
Experience developing de-identification strategies for PHI in research contexts
Experience working with Institutional Review Boards (IRBs) on data security for human subjects research
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