Automation Operations Team Leader

Our Company will be prioritizing applicants who have a current right to work in Singapore, and do not require Our Company's sponsorship of a visa.

About AI Data Service and Operations (ADSO) Team The AI Data Service and Operations (ADSO) team is responsible for providing safety and non-safety data annotation services and search operation services for all of the company's international products, which can also help international products build their own data ecological security.

Responsibilities

1. Workflow & Team Management: Responsible for managing multi-project workflows and team collaboration rhythms. Coordinate AI model guidance, prompt iteration, and diagnostic optimization to drive continuous improvement in response efficiency and output quality within high-frequency business scenarios.
2. Process Optimization & Technical Guidance: Deep dive into business processes and model application scenarios to identify key bottlenecks in prompt design, problem diagnosis, tool usage, and collaboration. Guide the team in designing and optimizing reusable prompt frameworks, methodologies, and internal solutions to enhance execution efficiency and technical consistency.
3. Toolchain Evolution & Problem Diagnosis: Utilize experimental results, business data, and model performance to drive the evolution of internal toolchains, such as Auto-Root Cause Analysis (Auto-RCA) and Auto-Prompt Agents. Refine diagnostic mechanisms for complex issues to improve the team's ability to analyze and resolve model failures, logical anomalies, and hallucinations.
4. Methodology & Capacity Building: Establish and continuously improve methodologies for prompt architecture, evaluation standards, review mechanisms, and technical training. Summarize and institutionalize best practices to promote knowledge replication and empowerment across the team.

Minimum Qualification(s)

1. Education & Experience: Bachelor’s degree or above; 3+ years of experience in AI/LLM development, AI data operations, or AI product operations. Proven ability in team collaboration or project leadership.
2. Prompt Engineering: Strong Prompt Engineering skills, with the ability to independently design prompt strategies and build evaluation or optimization workflows to improve model performance and operational efficiency.
3. Analytical Skills: Excellent data analysis, problem deconstruction, and abstraction skills. Able to identify and define problems based on data and drive them toward resolution.
4. Technical Proficiency: Familiarity with Python or SQL to support automated evaluation, process optimization, or related data analysis tasks.
5. Language: Fluent in English (reading and writing) as a working language.
6. Soft Skills: Clear logic and rigorous execution. Able to adapt to a fast-paced, multi-tasking environment with excellent communication and collaboration skills.

Preferred Qualification(s)

1. Academic Background: Degree in Computer Science, Statistics, Engineering, Linguistics, Philosophy, or other STEM-related fields.
2. Domain Expertise: Experience in Trust & Safety, content moderation, or classification labeling.
3. Technical Depth: A solid understanding of Transformers, tokenization mechanisms, and the fundamental principles of Large Language Models (LLMs) to effectively gauge model capability boundaries.
4. Implementation: Experience in AI application deployment, AI project implementation, or team management.