Staff Security Engineer, Privacy Engineering & AI

The Security and Privacy Architecture team sits within Uber's Security organization and serves as the technical privacy authority across the company. We own architectural reviews for new platforms and products, define privacy engineering standards, and increasingly build tooling and prototypes ourselves to prove out solutions before handing off to product engineering teams for productionization.
Why this role exists: Uber is accelerating AI adoption: LLM-powered features, agentic systems, internal AI tooling, and AI-driven advertising products. We need a senior engineer who can both define the privacy and security guardrails for these systems and demonstrate they work with functional prototypes. This gap cannot be filled by advisory-only roles; we need someone who writes code and deliver PoCs.
Key projects and focus areas:
1. Privacy controls for Uber's internal LLM platform and agentic AI integrations (data handling boundaries, prompt/log sanitization, model evaluation data governance)
2. Anonymization tooling for unstructured and multimedia data (video, audio, images) - moving beyond regex to ML-based approaches
3. Scalable governance frameworks for AI data pipelines, including approval workflows for agentic systems
4. Automation of manual privacy review and security processes into reusable platform capabilities
5. High-stakes architectural privacy reviews for ads systems, data platforms, streaming infrastructure, and new product launches
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Team structure: You'll be part of the Security and Privacy Architecture team, working alongside other senior security and privacy engineers. You'll collaborate daily with Privacy Legal, Product, Infrastructure, Compliance, and Ads teams. This is a Staff IC role: no direct reports, but significant mentorship and technical influence expected.
Visibility and career growth: This role has direct visibility with Security and Privacy leadership. The person in this seat will shape the technical standards governing how AI is built at Uber. There's a clear path toward Principal Engineer for someone who establishes themselves as the go-to technical authority on AI privacy. If the scope grows, there's also the possibility of building out a small team.
Who thrives here: Someone who's equally comfortable whiteboarding an architecture with a VP and writing a Python prototype that detects PII in audio transcripts. You should be energized by ambiguity: many of the problems in AI privacy don't have established playbooks yet, and you'll be writing them.
For San Francisco, CA-based roles: The base salary range for this role is USD$232,000 per year - USD$258,000 per year. For Seattle, WA-based roles: The base salary range for this role is USD$232,000 per year - USD$258,000 per year. For Sunnyvale, CA-based roles: The base salary range for this role is USD$232,000 per year - USD$258,000 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 https://jobs.uber.com/en/benefits.