Technical Business Analyst (AI & LLM)

About the Role We are seeking an experienced Technical Business Analyst to join our client team. In this pivotal role, you will work at the intersection of educational technology, digital transformation, and large-scale government operations. You will partner with cross-functional teams to design human-centered digital solutions that shape student placement experiences. A key focus of this role is bridging the gap between business operations and technical architecture, while progressively exploring how AI and Large Language Models (LLMs) can optimize and automate business rules testing. Key Responsibilities Process Mapping & Operational Support: Develop a deep understanding of complex student placement processes, policies, and underlying systems. Provide direct operational support during critical placement exercises. Requirements Elicitation: Partner with business teams using design thinking, human-centered methodologies, and visual tools to translate citizen and agency needs into actionable user stories and functional specifications. Tech Stack Alignment: Evaluate and recommend digital solutions aligned with directions (cloud-first, enterprise architecture principles, and the Singapore Government Tech Stack). Quality Assurance & Code Awareness: Review vendor-delivered code (specifically Go ) for security, performance, and maintainability. Assist with quality gate practices within DevOps pipelines. System Monitoring & Troubleshooting: Analyze application logs and system metrics ( ELK Stack, Splunk , or equivalent) to diagnose issues and ensure operational stability. AI Innovation: Support the team's roadmap to integrate AI/LLM capabilities, particularly around using prompt engineering to automate business rules testing and edge-case validation. Knowledge Management: Document workflows, business logic, and system configurations to retain crucial institutional knowledge. Technical Competencies & Requirements Experience: Minimum 5 to 7 years of experience in technical business analysis roles within Agile, product-centric environments. Core Tech Skills: Proficient with Git platforms (GitHub, GitLab, or Bitbucket) and familiar with CI/CD and DevOps pipelines. System Architecture: Working knowledge of API integrations, data flows, and modern system architectures. Log Management: Practical experience with log monitoring tools like ELK stack or Splunk. LLM & Prompt Engineering: Hands-on experience designing and optimizing prompts (e.g., GPT, Claude) within enterprise workflows or quality assurance testing. Added Advantage: Candidates who have actively applied LLMs to automate test case generation from complex natural language business rules will be given significant weight. Personal Attributes & Soft Skills Exceptional Communicator: Able to influence without authority and facilitate meaningful alignment between technical developers and non-technical business stakeholders. Thrives in Ambiguity: Analytically minded, pragmatic, and comfortable multitasking across concurrent workstreams. Steady Under Pressure: Detail-oriented and dependable during time-sensitive, large-scale operational runs. Forward-Thinking: Possesses a continuous-improvement mindset—always questioning manual processes and looking for smarter ways to leverage technology.