AI Innovation Lead and Knowledge Base Specialist
On-siteSingapore, Singapore
Job Summary
Explore business processes and testing workflows to identify opportunities for AI and automation that improve test coverage, stability, and cycle time. Develop practical recommendations, define expected value and risks, and collaborate on proof-of-concept projects showcasing AI-enabled testing solutions. Build and manage knowledge systems by training new agents, scaling knowledge bases using RAG techniques, and maintaining scalable automation frameworks across API, UI, and performance domains. Engage with stakeholders to frame problems, translate technical concepts into business language, and support project management for PoC delivery. Stay current with advances in testing, DevOps, and AI to share learnings and contribute to team best practices.
Required Qualifications
- Experience building or working with automation frameworks and CI/CD pipelines
- Familiarity with testing tools such as Selenium, Playwright, Cypress, SoapUI, Rest Assured, or JMeter
- Programming experience in Python and/or JavaScript/TypeScript
- Basic understanding of version control (e.g., GitHub) and modern DevOps practices
- Exposure to test management tools and loosely coupled automation architecture concepts
- Bachelor's degree in engineering, IT, computer science, or related field (or equivalent hands-on experience)
- 1-3 years of experience in automation testing, QA, or related technical roles (or strong academic projects demonstrating relevant skills)
- Strong problem-solving mindset and ability to think creatively about testing challenges
- Experience or demonstrated ability in stakeholder communication and translating technical concepts for business audiences
- Familiarity with modern software development and testing lifecycles
- Basic understanding of non-functional testing (performance, reliability, usability) and test data management
- Foundational knowledge of AI concepts relevant to testing (e.g., classification, anomaly detection, NLP) and interest in practical applications
- Excellent communication skills and enthusiasm for cross-functional collaboration
- A proactive learner eager to grow in AI-driven testing and automation
- Someone who thrives in collaborative environments and enjoys working across teams
- A candidate with curiosity about emerging technologies and a commitment to staying current with industry trends
Desired Qualifications
- Java knowledge is a plus
- Curiosity about AI applications in testing (e.g., predictive test selection, defect risk scoring, intelligent locator healing)
- Willingness to learn about data pipelines, feature engineering, and model evaluation basics
- Interest in exploring AI/ML tools and frameworks such as LangChain, RAG, or similar technologies
- Interest in training and improving AI agents using retrieval-augmented generation (RAG) techniques
- Ability to support business users and troubleshoot AI agent performance issues
- Openness to learning AI orchestration frameworks and best practices
- Familiarity with Automotive or trading business processes
- Exposure to process areas such as O2C, S2P, or similar
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