You will work within the Explanation and Guidance team to improve the legal process page and evolve AI-driven explanation features. The role involves a mix of frontend and backend development, focusing on performance, usability, and integrating LLMs to assist users.
Develop fullstack solutions for monetization strategies with a primary focus on frontend development using React, TypeScript, and GraphQL. Collaborate with product, design, and data teams to reduce friction in user acquisition and optimize subscription plans.
Lead the Trust & Safety operations team, managing people, performance metrics, and stakeholder relationships to ensure quality and legal compliance. Drive the integration of AI into operational workflows and collaborate with product, engineering, and legal teams to optimize moderation and privacy processes.
The Legal Operations Assistant will execute daily operational tasks, including processing legal information and maintaining data accuracy within established deadlines. They will also identify process bottlenecks and contribute to the adoption of automation tools to improve operational efficiency.
Act as the technical and people management lead for the Legal team, overseeing the modernization of a Python 2.7 legacy system into microservices. Ensure platform reliability, security, and observability while managing high-throughput event processing and stakeholder communication.
The engineer will work on Search and EVAL teams to handle search problems, quality evaluation, and A/B testing for search and recommendation flows. They will design and analyze experiments independently while integrating AI tools deeply into their daily workflow.
Act as the security focal point for B2B products, ensuring secure development through threat modeling and security reviews. Lead the implementation of robust authentication, SSO, and secure coding guidelines across the engineering lifecycle.
Build and manage the semantic data layer to ensure consistent business rules and data governance across the company. Act as a bridge between data infrastructure and business stakeholders to translate requirements into efficient dimensional models.
Design, develop, and maintain large-scale data ingestion and transformation pipelines using GCP. Collaborate with multidisciplinary teams to transform raw data into reliable analytical assets for business decision-making.
Act as a strategic link between the Engineering Platform and Product Areas to improve reliability, availability, and scalability. Implement SRE agendas including SLOs, incident management, and the adoption of Golden Paths within product teams.
Collaborate with cross-functional teams to design, develop, and implement innovative technological solutions. Actively participate in technical decision-making processes while promoting a culture of continuous learning and knowledge sharing.
The SRE Partner will act as a strategic link between the engineering platform and product teams to improve reliability, scalability, and operational maturity. Responsibilities include defining SLOs, managing incident responses, and promoting the adoption of platform resources to reduce operational risk.
You will be responsible for managing the semantic data layer and ensuring data governance to provide consistent business logic across the company. Additionally, you will collaborate with stakeholders to translate business requirements into efficient dimensional models while leveraging AI to automate data processes.
The Data Engineer will be responsible for designing, developing, and maintaining data ingestion, processing, and storage systems. This role ensures scalability, governance, and performance in a dynamic and collaborative environment.
