Company Overview:

TechX is a trailblazer in cloud computing and data analytics, dedicated to empowering businesses in the banking, financial services, and enterprise sectors. Our flagship product, XData, revolutionizes data analytics by delivering advanced insights and innovative solutions that drive impactful outcomes.

Description:

QC Engineer - HCM

Description:

You will be part of a project developing an intelligent AI Agent in the form of a RAG (Retrieval Augmented Generation) Chatbot and Voicebot, designed to provide public information and customer support for XgenAI. The system integrates advanced technologies such as Natural Language Processing (NLP/NLU), RAG from a Knowledge Base, Speech-to-Text (STT), Text-to-Speech (TTS), and Large Language Models (LLM) on the AWS Bedrock platform.

Key Responsibilities:

1. Planning and Strategizing:

• Deeply analyze functional and non-functional requirements of the AI Agent to design and implement detailed and comprehensive testing strategies.
• Clearly define the quality standards that the AI product must meet (e.g., NLU accuracy, RAG precision, TTS naturalness, WER for STT, response time, AI ethical guidelines).

2. Test Creation:

• Develop detailed test cases and scenarios that simulate real-world usage of Chatbot and Voice Bot interactions to identify potential bugs, inaccuracies, and performance issues.

• Develop specialized test data sets for NLU intent/entity recognition, conversational paths, and STT/TTS quality evaluation.

3. Execution and Analysis:

• Execute designed test cases across various AI Agent functionalities (NLU, RAG, STT, TTS, LLM) and meticulously analyze results to pinpoint defects, AI model weaknesses, and data quality issues.

• Thoroughly evaluate response relevance, factual accuracy, and conversational coherence.

4. Reporting and Collaboration:

Document bugs and AI-related issues in detail within bug tracking systems (e.g., Jira), including clear reproduction steps, relevant input/output logs, and initial root cause analysis.

• Collaborate closely with Business Analysts and Developers to report bugs, discuss solutions, and support efficient bug resolution.

 5. Process Improvement:

• Continuously evaluate and refine the testing process, methodologies, and tools, especially within the challenging context of AI/ML quality assurance.

• Contribute to improving the quality of training data and AI output quality standards.

6. Bug Validation and Support:

• Ensure adherence to bug response SLAs and proactively validate customer-submitted bugs, particularly those related to the AI Agent's understanding or response quality
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Key Requirements:

• Experience in AI/ML Quality Assurance: Demonstrated knowledge and practical experience in testing AI/ML-driven applications, specifically Chatbot/Voicebot, Natural Language Processing (NLP/NLU), Speech-to-Text (STT), Text-to-Speech (TTS), and Large Language Models (LLM).

• Testing Techniques: Strong knowledge in various testing techniques and methodologies applicable to AI systems (e.g., black-box, white-box, performance, security, regression, and particularly AI-specific testing for accuracy, bias, and robustness).

• Test Planning and Strategy: Ability to develop comprehensive test plans, detailed test cases, and test scripts tailored for complex AI Agent functionalities. Experience in creating test strategies that cover all aspects of the AI development lifecycle, from data ingestion to model deployment. Understanding of risk-based testing to prioritize AI-related testing efforts effectively.

• Bug Tracking and Reporting: Proficiency in using bug-tracking systems like Jira, Bugzilla, or similar tools. Ability to accurately report defects with clear steps to reproduce, including specific AI inputs/outputs and environmental details.

• Technical Acumen: Familiarity with cloud platforms (preferably AWS, given the project's use of AWS Bedrock, S3, OpenSearch, RDS) and API testing tools (e.g., Postman). Basic understanding of data processing pipelines and vector databases.

• Communication and Collaboration: Excellent communication skills (both Vietnamese and English) to interact effectively with cross-functional teams, including developers, product managers, and especially Data Scientists and AI Engineers. A collaborative approach to working closely with technical teams to identify, reproduce, and resolve AI-related issues.

• Analytical and Problem-Solving Skills: Strong analytical skills to identify root causes of AI defects (e.g., NLU misclassifications, RAG hallucination, STT/TTS quality issues) and provide insights for process or model improvement. Ability to troubleshoot complex AI-related issues and make recommendations for corrective actions.

• Attention to Detail & Accuracy: Meticulous attention to detail, especially when validating AI responses for factual accuracy, grammatical correctness, and naturalness

Apply now and join our mission to transform data into meaningful business outcomes!

Due to the high volume of applicants, only shortlisted candidates will be contacted. We apologize for this inconvenience!