AI Privacy Engineer

Role Description

We are seeking an AI Privacy Engineer to design, implement, and maintain privacy-preserving AI systems and data governance practices. The ideal candidate will collaborate with AI, data, security, legal, and compliance teams to ensure that machine learning models and AI applications are developed and deployed in accordance with privacy regulations and organizational policies.

Key Responsibilities

• Design and implement privacy-by-design principles across AI and machine learning solutions.
• Evaluate AI systems for privacy risks and recommend mitigation strategies.
• Develop and maintain data anonymization, pseudonymization, and de-identification techniques.
• Implement privacy-enhancing technologies (PETs), including differential privacy, federated learning, and secure multi-party computation where applicable.
• Conduct Privacy Impact Assessments (PIAs) and Data Protection Impact Assessments (DPIAs) for AI initiatives.
• Ensure compliance with global privacy regulations such as GDPR, CCPA/CPRA, HIPAA, and other applicable data protection laws.
• Collaborate with AI engineers to build secure data pipelines and privacy-aware model training workflows.
• Define data retention, consent management, and data minimization practices.
• Monitor emerging AI privacy risks, regulations, and industry best practices.
• Support internal and external privacy audits and compliance initiatives.
• Develop privacy engineering standards, documentation, and technical guidelines.
• Provide technical guidance and training to engineering teams on AI privacy practices.

Qualifications

• Bachelor's or Master's degree in Computer Science, Information Security, Data Science, Artificial Intelligence, or a related field.
• 3+ years of experience in privacy engineering, AI/ML engineering, cybersecurity, or data governance.
• Strong understanding of machine learning workflows and AI model lifecycle.
• Experience with Python and data processing frameworks such as Pandas, Spark, or TensorFlow/PyTorch.
• Knowledge of privacy-enhancing technologies including:
• Differential Privacy
• Federated Learning
• Homomorphic Encryption
• Secure Multi-Party Computation
• Data Masking and Tokenization
• Familiarity with cloud platforms such as AWS, Azure, or Google Cloud.
• Experience implementing data governance and privacy controls.
• Knowledge of encryption, identity management, and secure software development practices.
• Excellent analytical, communication, and cross-functional collaboration skills.

Preferred Qualifications

• Experience with Generative AI or Large Language Models (LLMs).
• Knowledge of Responsible AI and AI governance frameworks.
• Familiarity with NIST AI Risk Management Framework, ISO/IEC 42001, ISO 27001, and SOC 2.
• Privacy certifications such as CIPP, CIPM, CIPT, or equivalent.
• Security certifications such as CISSP or CCSP are a plus.

Technical Skills

• Python
• SQL
• AI/ML Frameworks (TensorFlow, PyTorch, Scikit-learn)
• Privacy Engineering
• Data Governance
• Cloud Security
• Encryption Technologies
• API Security
• Data Loss Prevention (DLP)
• Kubernetes and Docker (preferred)
• Git and CI/CD

Soft Skills

• Strong problem-solving ability
• Attention to detail
• Risk assessment and decision-making
• Effective stakeholder communication
• Collaboration across engineering, legal, and compliance teams
• Continuous learning mindset

Success Metrics

• Reduction in AI privacy risks.
• Compliance with applicable privacy regulations.
• Successful deployment of privacy-preserving AI solutions.
• Timely completion of privacy assessments.
• Improved data governance maturity across AI initiatives.
• Positive audit and regulatory outcomes.