AI Agent PM

주요업무

| 이런 경험을 할 수 있어요 Real-world LLM Alignment: Gain rare, hands-on experience orchestrating customer-facing AI Agents that handle live customer traffic, optimizing alignment through continuous feedback loops. AI-Native Workflow Mastery: Immerse yourself in a culture that leverages AI across the board - from ideation and engineering to data analysis and documentation - making AI fluency a core part of how you work. Global AI Product Leadership: Build your career as a Global AI Product Manager by leading the End-to-End Product Lifecycle (Planning, Deployment, Operation, Improvement) based on user data from diverse languages and cultures. Data-Driven Decision Making: Develop the capability to derive quantitative Product Insights by analyzing hundreds of thousands of actual customer conversation logs using AI. Global Cross-Functional Leadership: Strengthen your leadership by collaborating with diverse functional organizations (Knowledge Management, CS Operations, Platform, Data Teams) and global stakeholders. | 우리는 이런 일을 해요 1. Product Roadmap & Alignment Strategic Alignment: Coordinate with Game Product, Engineering, and Operations teams prior to new feature launches or system changes to ensure the Agent is aligned with the latest Context. Roadmap Execution: Define the Product Roadmap to achieve key metrics (e.g., Deflection Rate, CSAT) and coordinate release schedules with development teams. Market & Technology Intelligence: Conduct competitive analysis on CS AI solutions and emerging LLM capabilities to inform the product strategy. 2. Agent Ops & Quality Control Continuous Monitoring: Monitor Agent responses in real-time to detect hallucinations and inappropriate answers. Resolve issues through Prompt/Instruction Tuning or by escalating to the appropriate teams. Edge Case & Safety Management: Identify unexpected user scenarios, adversarial inputs (e.g., jailbreaking attempts), and policy violations. Evaluate and strengthen safety guardrails to ensure the Agent handles unforeseen situations gracefully. Performance Optimization: Collaborate cross-functionally with Knowledge Base, CS Ops, Contents, and Data Teams to update Grounding Resources and address root causes of performance issues. Evaluation Management: Build and maintain curated evaluation sets (Golden Test Sets) covering typical user queries and edge cases. Continuously track metrics (Accuracy, Relevance, Groundedness) to ensure response consistency. 3. Data-Driven Insight & Risk Management Anomaly Detection: Detect sudden changes in User Query Patterns to identify potential system failures or bugs, promptly escalating them to Operation/Engineering teams. VOC Analysis: Surface Voice of Customer data from conversation logs to provide actionable insights that drive Product Improvement across the entire organization. | 이런 도구와 기술을 활용하고 있어요 Our team works hands-on with Frontier Models and modern SaaS tools daily. • LLM/MLLM: Almost Frontier Models (GPT, Claude, Gemini, Qwen, etc.) • Cloud Platforms: Azure, AWS, Google Cloud (including AI/ML managed services) • Data Solutions: Snowflake, BigQuery/BigLake, Firestore, Cosmos DB • Collaboration & Productivity: Jira, Slack, Confluence (w/ Atlassian Rovo), Google Workspace (w/ Gemini Pro, NotebookLM Pro), Claude Code • SaaS Integrations: Salesforce, Sendbird, Lokalise

자격요건

| 이런 분과 함께 하고 싶어요 Total Experience: 7+ years (with 5+ years in PM/PO roles) Business-Fluent English (Verbal & Written): Ability to discern subtle nuance and context in English text and apply that precision to Prompt Engineering - beyond conversational fluency. Hybrid Role Capability: Ability to balance the strategic planning ("Why") of a Product Owner with the execution and management ("How") of a Project Manager. Analytical Problem Solving: Ability to logically decompose complex issues and derive solutions based on Data. Technical Understanding: Working understanding of LLM Core/Application mechanisms (Token, Temperature, Context Window, CoT, Extended Thinking, Tool Calling, Grounding) and Prompt Engineering techniques.

우대사항

| 이런 경험이 있으면 더 좋아요 Experience or understanding of the iGaming or Regulated Business. Personal interest in Poker, iGaming or game theory - helpful for building empathy with our core user persona. Understanding of the Customer Support Domain or experience with CS System projects. Experience in planning, commercializing, and operating LLM-based Conversational AI services. Experience building or prototyping products using Agentic Coding tools (e.g., Claude Code, Antigravity, GitHub Copilot, Cursor). Experience with the Salesforce Ecosystem and data analysis skills using Python/SQL.

기술스택

Google-Firestore, AWS, Salesforce, BigQuery, Google-Cloud-Platform, LLM, Snowflake

채용절차

| 이런 여정을 거쳐 합류해요 영어 역량 검사(PC 환경) ▶ Culture Fit(전화인터뷰)&직무 적합성 검사 ▶ 실무 면접 ▶ 평판 조회 ▶ 처우 협의 ▶ 최종 합격 | 근무 형태 및 시간 근무 형태 : 정규직 (시용 3개월 종료 후, 정규직 전환 가능 대상 / 정규직 급여와 동일) 근무 시간 : 선택적 근무제 (출근시간 : 오전 9시 ~ 11시)