Software Engineer, Full Stack, Central Integrity
- Bellevue, Washington, United States +2 more
- On-site
- Posted Nov 10, 2026
INDUSTRYSoftware & InternetSaaS & Enterprise Software
Locations (3)
- Bellevue, Washington, United States
- Menlo Park, California, United States
- Seattle, Washington, United States
Responsibilities
- Lead the technical direction and end-to-end delivery of advertiser verification products and systems, from problem definition and architecture through implementation and rollout
- Set direction and goals for teams, lead major initiatives, provide technical guidance and mentorship to peers, and help onboard new team members
- Combine trusted signals, user-provided evidence, deterministic systems and AI/ML capabilities to improve verification quality and adapt the experience to different needs and risk levels
- Build intuitive user experiences and scalable backend services that help people and businesses establish their identity and demonstrate their connection to a business
- Establish testing, evaluation, monitoring, and rollout safeguards for production systems, including AI-enabled features
- Improve system reliability, performance, and scalability, and address technical debt that limits product development
- Provide technical guidance and mentorship, lead design and code reviews, and build alignment across teams while remaining hands-on in engineering delivery
- Establish ownership of components, features, or systems with expert end-to-end understanding
- Collaborate with cross-functional teams (product, design, operations, infrastructure) to build innovative application experiences
Requirements
- PhD or Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
- Experience in a Trust and safety
- Experience in a Risk engineering
- Experience in a Fraud prevention
- Experience in a Security engineering
- Experience in a Regulated-domain engineering
Skills
Programming experience in a relevant languageExperience building identity, authentication, verification, fraud prevention, or trust and safety productsExperience building detection, classification, or enforcement systems for abuse, fraud, or safety harms at consumer scaleExperience in trust and safety, risk, fraud, security, or regulated-domain engineeringExperience evaluating and addressing privacy, security, accuracy, and potential bias in data- or AI-enabled systemsExperience applying machine learning or LLM-based capabilities to production products, including evaluation, monitoring, fallback behavior, and quality improvementsExperience working on adversarial problems where bad actors actively adapt to countermeasuresExperience adhering to and implementing responsible, ethical AI practices
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