Software Engineer, Product - Central Integrity

Meta is seeking experienced engineers to join our Central Integrity team which exists to keep billions of people safe on Meta's platforms. We design and deploy systems that detect and disrupt harm at an unprecedented global scale, making this one of the largest deployments of AI for positive real-world impact anywhere in the industry. Our work safeguards critical areas including child and youth safety, fraud and scams, identity and authenticity and more while actively building defenses against novel frontier threats, such as autonomous AI agents and automated risk vectors. This represents some of the most technically demanding and high-stakes engineering and product at Meta, driven by a deeply mission-focused team. You'll combine strong engineering fundamentals with cutting-edge AI to build effective, adaptable solutions that stay ahead of evolving integrity and safety risks. If you are driven by hard technical challenges and want your work to deliver immediate, real-world impact, this is the team for you.

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

Qualifications

8+ years of programming experience in a relevant language OR 4+ years experience with a PhD Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience Programming experience in a relevant language Demonstrated experience driving change within an organization and leading complex technical projects Experience utilizing data and analysis to explain technical problems and provide detailed feedback and solutions Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies Experience building identity, authentication, verification, fraud prevention, or trust and safety products; or working on adversarial problems where misuse evolves over time Experience building detection, classification, or enforcement systems for abuse, fraud, or safety harms at consumer scale Experience in trust and safety, risk, fraud, security, or regulated-domain engineering Experience evaluating and addressing privacy, security, accuracy, and potential bias in data- or AI-enabled systems Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements) Experience applying machine learning or LLM-based capabilities to production products, including evaluation, monitoring, fallback behavior, and quality improvements Experience working on adversarial problems where bad actors actively adapt to countermeasures Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews) Experience developing reliable, scalable applications and improving quality through code reviews, testing, safe rollout, and proactive monitoring