Senior Privacy Engineer

Summary

Upstart is an AI lending marketplace that uses advanced technology to expand access to affordable credit. The Senior Privacy Engineer will build and operate privacy engineering services, embed privacy-by-design and data minimization controls, and develop tools that support responsible data use across products, data platforms, and machine learning systems.

Responsibilities

• Design, build, and operate privacy engineering services that support user control, data governance, anonymization, pseudonymization, retention, deletion, and auditability
• Implement privacy-by-design patterns and data minimization controls across Upstart’s products, services, data pipelines, and machine learning systems
• Build APIs, libraries, services, and developer tools that help engineering teams standardize privacy enforcement across the technology stack
• Partner with Security, Legal, Compliance, Product, Data, Machine Learning, and Infrastructure teams to translate privacy requirements into clear technical specifications
• Support privacy reviews, data flow assessments, and technical risk assessments for new products, data uses, and platform capabilities
• Improve the reliability, observability, and maintainability of privacy systems through testing, monitoring, documentation, and thoughtful technical design

Skills

• Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field, or equivalent practical experience, and 3+ years of experience in software engineering
• Experience building and operating production software systems using programming languages such as Python, Go, Java, Scala, C++, Rust, or similar languages
• Experience building APIs, microservices, libraries, or backend services that support data governance, privacy controls, security controls, or data platform capabilities
• Experience with at least two privacy or security domains such as anonymization, pseudonymization, data retention, deletion, data lineage, access control, encryption, audit logging, or data minimization
• Experience translating privacy, security, compliance, or data protection requirements into software systems or technical workflows
• Knowledge of privacy-by-design principles, privacy-enhancing technologies, purpose limitation, consent, retention, deletion, and data subject rights
• Experience with data governance systems, data catalogs, lineage tooling, personally identifiable information detection, redaction, or automated policy enforcement
• Experience supporting privacy reviews, threat modeling, data flow mapping, or technical risk assessments for production systems
• Experience working with machine learning systems, financial services, lending, or another regulated data environment
• Ability to communicate privacy engineering tradeoffs clearly across technical, legal, compliance, product, and business audiences

Qualifications

Must Haves

• Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field, or equivalent practical experience, and 3+ years of experience in software engineering
• Experience building and operating production software systems using programming languages such as Python, Go, Java, Scala, C++, Rust, or similar languages
• Experience building APIs, microservices, libraries, or backend services that support data governance, privacy controls, security controls, or data platform capabilities
• Experience with at least two privacy or security domains such as anonymization, pseudonymization, data retention, deletion, data lineage, access control, encryption, audit logging, or data minimization
• Experience translating privacy, security, compliance, or data protection requirements into software systems or technical workflows

Nice to Haves

• Knowledge of privacy-by-design principles, privacy-enhancing technologies, purpose limitation, consent, retention, deletion, and data subject rights
• Experience with data governance systems, data catalogs, lineage tooling, personally identifiable information detection, redaction, or automated policy enforcement
• Experience supporting privacy reviews, threat modeling, data flow mapping, or technical risk assessments for production systems
• Experience working with machine learning systems, financial services, lending, or another regulated data environment
• Ability to communicate privacy engineering tradeoffs clearly across technical, legal, compliance, product, and business audiences

Benefits

• Target bonuses
• Equity compensation
• Medical, dental, vision, and wellness resources for US employees
• 401(k) or Group Retirement Savings Plan with a company match of $2 for every $1 contributed, up to $15,000 annually (USD in the US, CAD in Canada)
• Employee Stock Purchase Plan (ESPP) with discounted stock purchase options for eligible employees (US only)
• Health Savings Account contributions from Upstart for eligible plans (US only)
• Life insurance and disability coverage
• Paid time off, sick leave, and company holidays, in line with local requirements
• Paid family and parental leave to support caregiving and major life moments (duration varies by country)
• Family-centered benefits to support fertility, parenthood, and caregiving needs
• Employee Assistance Program (EAP) offering mental health support and life-centered resources
• Financial planning tools and a financial concierge service (US only)
• Annual wellness allowance to support physical and emotional well-being and personal development
• Annual productivity allowance to invest in relevant tools and resources
• Connection and community through team events, all-company updates, and employee resource groups (ERGs)
• Onsite perks, including catered lunches and fully stocked micro-kitchens when working from one of the offices in the Bay Area, Austin, Columbus, and New York City
• The majority of work can be accomplished remotely
• Regular team onsites, with most teams meeting once or twice per quarter for 2-4 consecutive days at a time