Applied Artificial Intelligence Engineer (Advertising Agents)

Join our advertising team as an Applied Artificial Intelligence Engineer. In this role, you will design, develop, and optimize an AI-driven intelligent account hosting and optimization platform. You will work with LLMs, Multimodal Foundation Models, and related techniques to build AI advertising expert systems that autonomously diagnose accounts and auto-tune delivery. Your work will directly impact global advertisers on our platform, maximizing their willingness to spend and platform revenue.

• Design, develop, and optimize an AI-driven intelligent account hosting and optimization platform for advertising.
• Build the core "AI Account Manager" system to realize automated hosting, autonomous optimization, and intelligent scheduling of optimization across many advertiser accounts.
• Collaborate with cross-functional teams to transform AI account management capabilities into the platform's core commercial competitiveness.
• Bachelor's/Master's degree or higher in Computer Science, Artificial Intelligence, Data Science, or related fields
• Possess a basic understanding of fields such as ad delivery platforms or recommendation systems; fresh graduates are acceptable
• Familiar with building, deploying, and optimizing agentic systems in production environments
• Strong software-engineering fundamentals: production-quality code, asynchronous/concurrent programming, typed and data-modeled code, and a solid testing discipline
• Possess excellent analytical and complex problem-solving abilities
• Solid grounding in machine learning and AI fundamentals; familiar with advertising or recommendation system concepts
• Hands-on with harness engineering, structured/schema-validated LLM outputs, and integration with modern model APIs
• Experience with REST/API integration and building reliable long-running services; familiar with modern deployment tools such as Kubernetes
• Master LLMs, RAG, tool-use, memory handling, and agent orchestration (including MCP-style tool ecosystems)
• Industry Background: Algorithm experience in the field of ad delivery, with more than 2 years applying large-model capabilities to systems such as automated delivery, automated hosting, autonomous tuning, or automatic scheduling
• AI Production Experience: Experience landing commercial AI agents (agent-based systems), large-model instruction tuning, or multimodal models
• Business Acumen: Understanding of digital advertising mechanics and core metrics (CPA, ROAS, CVR, CTR, conversions) and of online A/B experimentation