About us
Gogolook is a leading TrustTech company founded in 2012 and listed on the Taiwan Stock Exchange in 2025 under the stock code 6902. With "Build for Trust" as its core value, the company has expanded its business from Asia to Europe and America. Gogolook’s AI technology is built on the world's largest database of digital scam data, encompassing phone numbers, websites, virtual currency wallet addresses, and other factors.
The company provides diverse anti-scam and fintech services for both consumers and businesses. Its anti-scam offerings include the digital anti-scam app "Whoscall" and a range of enterprise scam prevention solutions in combination with "ScamAdviser."
The Fintech BU empowers consumers through data-driven financial services and inclusive lending: Roo.Cash（袋鼠金融）offers transparent matchmaking for financial products like credit cards, while JUJI（招財麻吉）provides an innovative microloan service for rapid, convenient funding during urgent financial needs.
A foundation member of the Global Anti-Scam Alliance (GASA), Gogolook has also teamed up with a number of institutes such as the Taiwan National Police Agency Criminal Investigation Bureau, the Financial Supervisory Service of South Korea, Thai Royal Police, the Fukuoka city and Shibuya City government, the Philippines Cybercrime Investigation and Coordinating Center, and the Royal Malaysia Police and state government to fight scam, dedicated to creating a "scam-free environment."
Why you should join Gogolook
- Influential products: What we make are meaningful products that create values for society and defend against frauds.
- Emphasize self-growth: We encourage technical community activities, subsidize tickets for conferences and workshops so that learning is continuously supported by the company.
- Unleash your talent: We respect the professional opinions of everyone, encourage team members to discuss with each other, and make awesome products together.
- Transparent culture: We publicly share the company's information to all, every member can read and feedback, and become a part of participating in the proposal.
About the Role
Gogolook's Anti-Scam Common Services are the shared data and service platform behind Whoscall, ScamAdviser, and our enterprise anti-scam solutions. These services turn Gogolook's anti-scam data and AI capabilities into reusable APIs and agent-ready tools that internal teams and AI agents can easily integrate and use.
We're looking for an AI Product Lead to own the Common Services roadmap, prioritization, delivery, and adoption. Your primary customers will be internal PMs, BDs, and Engineers, and you'll work closely with engineering, data, research, and business teams to improve self-service data access, developer experience, and AI-enabled workflows. Your goal is to make shared capabilities easier to discover, integrate, and use, helping business units build anti-scam products faster while ensuring reliability, security, and responsible AI practices.
Responsibilities
Product Strategy & Roadmap: Define and manage the Common Services roadmap across data ingestion, reputation services, shared reporting, and AI-ready interfaces. Prioritize initiatives based on business needs, platform value, and technical feasibility, and drive delivery with engineering teams.
Internal Customer & Service Adoption: Work closely with internal PMs, BDs, and Engineers to understand their needs and turn recurring requests into reusable, self-service capabilities. Improve developer experience, documentation, onboarding, and integration efficiency.
Data Ingestion & Reputation Services: Lead product development for self-service data ingestion, including source registration, data import, and monitoring. Improve shared reputation services covering phone numbers, URLs, content, and report handling, ensuring reliable and consistent access across products.
AI-Ready Interfaces & Workflows: Define API and MCP tool capabilities that enable AI agents to securely access and interact with Gogolook's data and services. Establish clear integration contracts, evaluation criteria, and reliable agent-facing workflows.
Service Governance & Security: Define requirements for authentication, API keys, service accounts, and usage policies. Collaborate with security, data, and legal teams to ensure privacy, access control, auditability, and Responsible AI compliance.
Cross-Functional Delivery & Improvement: Collaborate with engineering, data, research, and business teams to manage delivery and continuously improve platform adoption, reliability, operational efficiency, and integration experience.
Requirements
5+ years of product management or comparable product ownership experience, with meaningful responsibility for platform, API, data, or developer-facing products.
Proven experience owning product roadmaps, managing priorities, and driving delivery across multiple stakeholders.
Strong understanding of platform product management, including reusable services, developer experience, and internal product adoption.
Sufficient technical fluency to collaborate with engineers on APIs, data pipelines, system integration, authentication, and architectural trade-offs.
Working knowledge of AI applications and agent-based workflows, with hands-on experience using AI tools to improve productivity or automate workflows.
Strong analytical, communication, and stakeholder-management skills, including the ability to use SQL and data to support product decisions.
Full professional proficiency in Mandarin and English, with the ability to communicate and produce clear product documentation in both languages.
Preferred Qualifications
Experience managing internal developer platforms, data platforms, API products, or shared services used across multiple teams.
Hands-on experience with MCP, tool calling, agent skills, or AI workflow automation, particularly building or integrating agent-facing tools.
Deeper understanding of AI/ML systems, including model evaluation, monitoring, and deployment considerations.
Familiarity with data ingestion, data governance, authentication systems (e.g., OAuth, JWT, API keys), and cloud data infrastructure such as AWS.
Experience in anti-scam, trust and safety, cybersecurity, fraud prevention, or related domains, or a background in software engineering, data engineering, or solutions engineering.
