Staff Privacy Engineer: Build Privacy-Preserving AI

Anthropic Limited; New York (NY); Hybrid; USD 405,000 - 485,000; Full time

Job summary

Anthropic Limited is seeking a senior privacy engineer to establish and lead the privacy engineering function within the Data Infrastructure team. You will design privacy-preserving architectures for AI systems, lead privacy reviews, and translate regulations into scalable technical controls at massive scale.

This role sits at the intersection of privacy engineering, AI safety, and distributed systems with high autonomy and broad influence across engineering, research, and product teams.

Qualifications

• 12+ years of software engineering experience.
• 3+ years leading large, complex projects as a technical lead.
• Proficiency in Python, Go, or similar languages.
• Experience applying privacy engineering principles in production systems.
• Experience with GDPR and CCPA and translating legal requirements into technical designs.

Responsibilities

• Design and implement privacy-preserving architectures for AI training and inference at large scale.
• Partner with researchers to implement privacy-preserving training methods.
• Build foundational privacy infrastructure including data discovery, access controls, and audit logging.
• Translate regulatory requirements into technical implementations and automated controls.
• Architect data governance systems for data lineage and retention.

Skills

Privacy engineering

Python

Go

Production systems

Threat modeling

Education

Bachelor’s degree

Tools

Privacy‑enhancing technologies

Open‑source tooling

AI privacy standards

Job description

Anthropic Limited is seeking a senior privacy engineer to establish and lead the privacy engineering function within the Data Infrastructure team. You will design privacy-preserving architectures for AI systems, lead privacy reviews, and translate regulations into scalable technical controls at massive scale.

This role sits at the intersection of privacy engineering, AI safety, and distributed systems with high autonomy and broad influence across engineering, research, and product teams.