AI Project Engineer  

1. Handle user requests by gathering, analyzing, and documenting detailed business and user requirements.
2. Translate business requirements into system and functional specifications, and coordinate with programmers/developers to ensure proper implementation.
3. Prepare Business Requirements Documents (BRD), Functional Specification Documents (FSD), UAT plans, scenarios, and test cases, as well as assist users throughout the UAT, training, and deployment preparation processes.
4. Identify and analyze application/system issues and evaluate existing processes to provide appropriate recommendations for improvement.
5. Provide troubleshooting and production support, and coordinate with technical teams to ensure timely and effective issue resolution.
6. Ensure proper system implementation and operational readiness by providing training, guidelines, and support to end users.
7. Collaborate closely with business users, developers, QA, project managers, and relevant stakeholders.
8. Utilize AI-powered tools to support requirements analysis, documentation, research, data analysis, process mapping, test case creation, and overall productivity enhancement.

Core Responsibility
Independently take a business problem from discovery to a testable and validated AI-enabled product prototype, with minimal dependency on separate BA, Product, Design, or Engineering resources during the early product development stage.

1. Conduct business and user discovery to understand problems, pain points, processes, and opportunities for AI-enabled solutions.
2. Translate business problems into clear product requirements, user journeys, user stories, acceptance criteria, and measurable success criteria.
3. Conduct product and competitor research and determine how AI can effectively address the identified business problem.
4. Design the end-to-end solution, including AI workflow, user flow, system interaction, prompts, RAG/agent approach, human fallback, and required integrations. Create wireframes and interactive UI/UX prototypes using Figma, Figma Make, or equivalent tools.
5. Independently build working AI-assisted prototypes/MVPs using tools such as Lovable, Bolt, Replit, Cursor, or equivalent.
6. Connect prototypes with APIs, data sources, and basic integrations to create a realistic and testable product experience.
7. Conduct functional testing, user testing, prompt testing, and AI evaluation to validate whether the prototype solves the intended business problem.
8. Evaluate prototype performance based on accuracy, hallucination, usability, latency, cost, and user feedback. Iterate and improve the prototype based on testing and validation results.
9. Demonstrate the validated prototype to business and technical stakeholders and communicate its capabilities, limitations, and recommended next steps.
10. Prepare clear product and technical specifications so that validated solutions can be efficiently handed over to the Engineering team for production.
11. Collaborate with Product, Business, Engineering, QA, Design, and other stakeholders while maintaining ownership of the early-stage product development process.