AI Search and Retrieval Principal Engineer

Description

Summary: This role involves acting as a hands-on builder and technical leader to define long-term architecture and make key technology decisions for AI search and retrieval systems. Highlights: 1. Define future search stack and design scalable, cloud-native search architecture 2. Design and implement Knowledge Graph architecture for intelligent retrieval 3. Build production-grade systems on Google Cloud Platform **Our Client is currently hiring a AI search and retrieval Principal Engineer to join their amazing team**About the company: Founded in 2017, they are a leading expert network and primary research platform that connects businesses with vetted subject\-matter experts for calls, surveys, and longer engagements. The platform combines AI\-powered search with human expertise to deliver fast, accurate, and scalable solutions for knowledge access. About the role/What you'll do: You will act as both a hands\-on builder and a technical leader within a mid\-sized team, defining long\-term architecture and making key technology decisions. Search Architecture Strategy:* Evaluate and define the future search stack (technology selection is part of the role). * Design a scalable, cloud\-native search architecture from first principles. * Decide between and combine approaches such as: * Keyword search * Vector search * Hybrid retrieval * Graph\-based retrieval * LLM re\-ranking * Design indexing, data modelling, and ranking strategies. * Define measurable relevance and quality frameworks. Knowledge Graph \& Intelligent Retrieval: * Design and implement a Knowledge Graph architecture modeling entities and relationships. * Define graph schema, linking strategies, and enrichment workflows. * Combine graph\-based signals with semantic search and ranking models. * Build extraction pipelines on top of frontier models (OpenAI, Gemini). * Develop modern recommendation systems leveraging structured \+ unstructured data. **Data \& Cloud Infrastructure (GCP\-first):** * Architect retrieval pipelines on Google Cloud Platform (GCP). * Design data pipelines and feature stores using BigQuery or alternative analytical systems. * Ensure scalability, observability, and cost efficiency. * Build production\-grade systems, not experiments. Requirements:* 5\+ years building and scaling production search or retrieval systems. * Strong Python skills. * Strong experience designing search architectures, not just operating them. * Experience evaluating and selecting search technologies. * Experience with semantic search and embeddings\-based retrieval. * Experience building pipelines on top of frontier LLMs (OpenAI, Gemini). * Experience leading technical initiatives in mid\-sized teams. * Experience working with cloud\-native systems (GCP). What they offer: Tenure Gifts \- Vouchers, extra holiday and sabbaticals for each year of employment. Health insurance. Enhanced Maternity \& Paternity pay. Meal allowance. Training budget. Corporate Events \- From quarterly gatherings to their annual winter \& Summer parties, they love to celebrate, collaborate and have fun together! Want to know more? Get in touch with us