Technical Solution Engineer

This Support Engineer role within the Product department at AppsFlyer's San Francisco office provides technical support to customers, troubleshooting issues and ensuring customer satisfaction. The role requires strong problem-solving skills and knowledge of AppsFlyer's products.

Provides technical support and solutions to partners, ensuring successful integration and usage of AppsFlyer's platform.

This Support Engineer role within the Product department at AppsFlyer's Beijing office provides technical support to customers, troubleshooting issues and ensuring customer satisfaction. The role requires strong problem-solving skills and knowledge of AppsFlyer's products.

This Account Manager role manages post-sales client relationships for StackAdapt's programmatic advertising platform, focusing on campaign management, optimization, and client retention. The role involves designing campaign strategies, setting up/trafficking campaigns on the StackAdapt DSP, providing performance reporting, and identifying upsell opportunities. Requires 3+ years of RTB/programmatic experience and proven client relationship management skills.

This role serves as a strategic bridge between Appier's product applications, client data, and business requirements, architecting and implementing solutions using existing products. Requires SQL and Python for data extraction and modeling, dashboard development with Tableau or Looker, and experience with A/B testing and data governance. The consultant translates client feedback into product requirements and collaborates with Product, Customer Success, and Sales teams.

This role focuses on owning agent features end to end, from problem definition and design to shipping and measuring quality in production. The scientist will contribute to the design, development, and productionization of enterprise AI agents including Marketing, Strategy, Data Analysis, and Sales and Service agents, building agent capabilities as reusable skills and MCP tools. Requires 2+ years of experience in ML or software engineering, hands-on experience building at least one LLM or agent application end to end, and strong SQL and data reasoning skills.

This role focuses on developing and deploying machine learning models and evaluation frameworks for enterprise AI solutions, with a strong emphasis on LLM output quality and A/B testing. The scientist will work end-to-end from problem definition to production, collaborating with PMs and engineers, and will also monitor post-launch performance and communicate risks. Requires a Master's or PhD in a relevant field, at least 2 years of ML experience, and hands-on experience with classification, regression, ranking, retrieval, and LLM-as-a-judge evaluation.