AI Innovation Lead and Knowledge Base Specialist

Singapore, sgSenior1-3 years

Company Description

🏢 About Bosch Group

The Bosch Group is a leading global supplier of technology and services. It employs roughly 418,000 associates worldwide. The company generated sales of 90.3 billion euros in 2024. Its operations are divided into four business sectors: Mobility, Industrial Technology, Consumer Goods, and Energy and Building Technology. With technology that is “Invented for life,” Bosch wants to help improve quality of life and conserve natural resources. The Bosch Group comprises Robert Bosch GmbH and its roughly 490 subsidiary and regional companies in over 60 countries. At 136 locations across the globe, Bosch employs some 87,000 associates in research and development.

🏢 About Robert Bosch (South East Asia)

As the Bosch Group's regional headquarters in Singapore for Southeast Asia, Robert Bosch (South East Asia) Pte Ltd has represented the Group's interests across the region since 1923. With diversified businesses in Mobility Aftermarket, Industrial Technology, Consumer Goods, and Building Technology. Robert Bosch (SEA) Pte Ltd includes the Asia Pacific headquarters for Mobility Aftermarket, Building Technology, and Industrial Technology, as well as the Southeast Asia R&D setup for Corporate Research, Advance Engineering Centre, and Bosch Business Innovations, Bosch's in-house innovation and startup incubation network. At Bosch, we are committed through our EVP ensuring all our associates to GROW, ENJOY and INSPIRE during their journey with us.

Job Description

💼 Role Overview

As an AI Innovation Lead and Knowledge Base Specialist Intern, you'll work alongside our AI and testing teams to explore how artificial intelligence can transform our testing processes. You'll gain hands-on experience identifying opportunities, building solutions, and collaborating with stakeholders to drive meaningful improvements in test coverage, stability, and efficiency.

🎯 What you will do (Key Responsibilities)

Discover AI Opportunities
- Explore business processes and testing workflows to identify where AI and automation can make a real impact on test coverage, stability, and cycle time.
- Develop practical recommendations and roadmaps; learn to define expected value, risks, and success metrics.
- Collaborate on proof-of-concept (PoC) projects that showcase the business value of AI-enabled testing, such as predictive test selection, defect risk modeling, and intelligent test data generation.
Build and Manage Knowledge Systems
- Support the training of new agents and help scale our knowledge base using retrieval-augmented generation (RAG) techniques.
- Contribute to designing and maintaining scalable testing and training automation frameworks and pipelines.
- Help implement comprehensive test suites across API, UI, performance, and non-functional testing domains.
- Learn to integrate automation into CI/CD workflows, ensure traceability to requirements, and apply engineering best practices including version control, code reviews, and static analysis.
Engage with Stakeholders and Teams
- Work as a bridge between business teams and our AI group, helping to frame problems, clarify requirements, and align solutions with business goals.
- Practice translating technical concepts into clear business language and communicate progress through updates and dashboards.
- Support project management for PoC delivery, including solution design, rollout, testing, and measuring business impact.
Think Creatively and Solve Problems
- Explore innovative approaches to testing challenges, such as AI-assisted regression optimization, autonomous UI healing, and log analytics for root cause analysis.
- Offer thoughtful feedback that helps improve our test systems, data, and processes.
Stay Current and Grow
- Keep up with the latest advances in testing, DevOps, and AI; share what you learn and contribute to team knowledge and best practices.
- Identify opportunities for innovation and support account teams with new solutions and ideas.

Qualifications

👤 What We’re Looking For (Qualifications & Skills)

Process Automation Fundamentals
- Experience building or working with automation frameworks and CI/CD pipelines (or willingness to learn).
- Familiarity with testing tools such as Selenium, Playwright, Cypress, SoapUI, Rest Assured, or JMeter.
- Programming experience in Python and/or JavaScript/TypeScript; Java knowledge is a plus.
- Basic understanding of version control (e.g., GitHub) and modern DevOps practices.
- Exposure to test management tools and loosely coupled automation architecture concepts.
AI and Automation Interest
- 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.
Knowledge Base and AI Agent Support
- 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.
Domain Knowledge (Preferred)
- Familiarity with Automotive or trading business processes is advantageous.
- Exposure to process areas such as O2C, S2P, or similar is a plus.
Education and Background
- 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).
Professional 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.
Other Qualifications
- 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.