Privacy Engineer

About the Company

Unified Intelligence is transforming enterprise AI collaboration through its Privacy-AI infrastructure. Built around its patented Adaptive Collaborative Learning (ACL) technology, the company helps organizations unlock insights from siloed data without moving raw or sensitive information. With established momentum across Southeast Asia and the Middle East & North Africa, the organization is focused on enabling secure, privacy-first AI collaboration across enterprises.

Role Overview

The company is looking for a highly capable Privacy Engineer to contribute to advanced Privacy Enhancing Technologies (PETs). This position is suited to someone with practical knowledge of technologies such as Private Set Intersection (PSI), Multi-Party Computation (MPC), Homomorphic Encryption (HE), Differential Privacy (DP), Federated Learning, and data anonymization. The role calls for a strong base in applied cryptography or privacy engineering, along with the ability to work closely with decision scientists and interact directly with clients.

What You Will Work On

• Building systems in which sensitive data remains protected at all times.
• Designing workflows where computation is distributed across parties rather than centralized.
• Creating mechanisms that enforce privacy mathematically.

Key Responsibilities

• Develop and fine-tune APSI-based Private Set Intersection solutions.
• Architect and implement secure aggregation approaches using MPC.
• Build and apply differential privacy techniques.
• Analyze the balance between privacy protection and system performance.
• Assess and recommend suitable privacy-enhancing technology options.
• Create, develop, and test prototypes for privacy-preserving technologies.
• Present research findings clearly to relevant stakeholders.
• Translate research ideas into practical product capabilities.
• Partner with machine learning and backend engineering teams.

Requirements

• 5 to 10 years of experience in applied cryptography, privacy engineering, or a closely related area.
• Strong conceptual and practical understanding of cryptography and privacy-preserving methods.
• Experience working hands-on with one or more of PSI, MPC, HE, DP, Federated Learning, or data anonymization.
• Comfort with Python and/or systems languages such as Rust or C++.
• Bachelor’s or Master’s degree in Computer Science, Cryptography, Mathematics, or a similar field; a PhD is a strong advantage but not required.
• Excellent analytical and critical reasoning abilities.
• High attention to detail, especially in environments where security is critical.
• Capability to examine edge cases, threat models, and likely attack paths carefully.
• Independent, self-motivated approach to solving complex technical problems.
• Strong communication and teamwork skills across multidisciplinary, cross-functional groups.

Additional Information

This position is based in Singapore and is a full-time, onsite role. The salary or stipend has not been specified in the source information.