About the Role
As a fast-growing startup building a next-generation platform for the gig economy, we are looking for an AI Engineer to develop our AI interview system as well as to extend our long-term AI roadmap. You will build intelligent systems that not only automate recruitment but also streamline internal operations. This is a "build-from-zero" role in a collaborative, hands-on environment.
Key Responsibilities
AI Product & Feature Development (~60%)
· AI Interview Engine: Design and deploy conversational agents using Gemini and Vertex AI to conduct automated screenings and evaluate candidate fit.
· Operational AI (SOP Generation): Build LLM-driven workflows that transform raw process notes into structured Standard Operating Procedures (SOPs).
· Intelligent Data Retrieval: Develop RAG (Retrieval-Augmented Generation) systems or newer systems to allow staff to query internal documentation and databases using natural language.
· Evaluation & Testing: Implement A/B testing and evaluation frameworks to measure the accuracy and impact of AI-generated outputs.
AI Infrastructure (~40%)
· Hybrid Data Architecture: Manage and optimize data flows between PostgreSQL (structured logic), MongoDB (unstructured transcripts/SOPs), and BigQuery (long-term analytics).
· Vector Ops: Implement and maintain vector databases and embeddings (e.g., Gemini Embeddings) to power semantic search and retrieval across the platform.
· Backend Integration: Collaborate with engineering to build robust APIs and ensure seamless integration with our Flutter frontend.
· Scalability & Governance: Monitor AI costs and performance, ensuring data privacy and PII handling follow best practices.
Additional Scope (as the data function grows)
· Support AI needs for product experimentation and growth initiatives.
· Document AI models, pipelines, and business logic for team knowledge sharing.
· Stay up-to-date with new AI tools and best practices; suggest improvements to our stack as we scale.
· Experience: 3+ years of experience in AI engineering, backend engineering, or a closely related technical role.
· Generative AI: Strong proficiency with Large Language Models (LLMs), specifically the Gemini API and prompt engineering.
· Database Management: Hands-on experience with PostgreSQL and MongoDB; knowledge of how to structure data for AI consumption.
· Cloud Infrastructure: Proficiency in the Google Cloud Platform (GCP) ecosystem (Vertex AI, Cloud Functions, BigQuery).
· Technical Literacy: Awareness of software development practices including APIs, Git, and collaborating with Flutter/Frontend teams.
· Startup Mindset: Proactive, self-motivated, and comfortable "wearing multiple hats" to build systems from scratch.
Nice-to-Haves
· Agentic Frameworks: Experience with LangChain, LlamaIndex, or similar tools for building complex AI agents.
· Vector Search: Exposure to vector databases (e.g., Pinecone, Vertex AI Search) for high-performance data retrieval.
· Domain Experience: Prior work in marketplace platforms, HR-tech, or business process automation.
Other benefits will be based on Taiwan Employment laws.
