AI Engineer

As a fast-growing startup building a next-generation platform for the gig economy, Flexii is 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

• 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

• 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.

Requirements

• 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.

What We Offer

• The opportunity to shape the AI strategy of a scaling startup.
• A collaborative environment where your work directly impacts product and operational efficiency.