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Staff Security Engineer, Privacy Engineering & AI

The Security and Privacy Architecture team is Uber's technical privacy authority. We lead architectural reviews, define privacy engineering standards, and build prototypes that prove out privacy solutions before they're productionized. This role focuses on the intersection of privacy and AI: you'll design controls for LLM-based products, agentic systems, and unstructured data pipelines, and build working PoCs that demonstrate measurable impact. It's a high-visibility position where you'll shape how Uber adopts AI safely and turn one-off privacy problems into scalable platform capabilities.

---- What the Candidate Will Do ----

Design and prototype privacy and security controls for AI systems prompt/log handling, fine-tuning data pipelines, vector stores, and agentic tool integrations.

Lead privacy design reviews and architectural assessments for high-impact systems including large-scale data platforms, real-time streaming infrastructure, advertising systems, and new AI products.

Build working anonymization PoCs for unstructured data and multimedia, going beyond regex to handle complex entity types, multi-locale data, and contextual identifiers.

Identify recurring manual privacy/security processes and convert them into scalable automations, templates, and platform capabilities.

Partner with Security, Privacy Legal, Product, Infrastructure, Compliance, and Ads teams on complex privacy workstreams; mentor engineers on privacy-by-design and safe AI system design.

---- Basic Qualifications ----

• Bachelor's degree in Computer Science, Engineering, Information Security, or a related technical field.

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You should be able to walk us through your technical approach and design decisions in depth.

---- Preferred Qualifications ----

Experience building privacy/security controls for AI/ML systems: LLM-based products, agentic systems, model evaluation pipelines, or enterprise AI tooling.

Hands-on experience with PII detection, redaction, or pseudonymization for unstructured data or multimedia (video, audio, images), including experience with NER models, ML-based approaches, or computer vision for de-identification.

Experience with data deletion architecture

deletion propagation, derived data cleanup, backup/restore, legal hold, and retention enforcement.

Background in privacy-sensitive domains: adtech, autonomous vehicles, financial services, identity, marketplace data, or cross-border data sharing.

For San Francisco, CA-based roles: The base salary range for this role is USD$232,000 per year

For Seattle, WA-based roles: The base salary range for this role is USD$232,000 per year

For Sunnyvale, CA-based roles: The base salary range for this role is USD$232,000 per year

For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan.

You will also be eligible for various benefits. More details can be found at the following link.

Uber's mission is to reimagine the way the world moves for the better. Here, bold ideas create real-world impact, challenges drive growth, and speed fuels progress. What moves us, moves the world - let's move it forward, together.

Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.

If you have a disability or special need that requires accommodation, please let us know by completing this form.

Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.