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Generative AI Engineer

Charlotte Tran

Full-time · Job · London

About the role

Have you ever wanted to build AI systems that actually go to production — not just demos? We ship LLM-powered features to 8,000 paying users every month, and every one of them needs to work reliably, handle edge cases gracefully, and meet strict latency requirements. Our product is an AI writing assistant for technical documentation teams. You'll work on the core generation pipeline: retrieval-augmented generation, context window management, output formatting, and citation accuracy. The stack is LangChain, FastAPI, and a mix of OpenAI and open-source models via Hugging Face. This role is ideal for someone who's moved past the excitement phase of LLMs and is now interested in the engineering discipline of making them production-grade. We ship weekly, we measure everything, and we take reliability seriously.

Responsibilities

  • Build and improve RAG pipelines for technical document generation
  • Optimize LLM inference for latency and cost across multiple providers
  • Design evaluation suites for generation quality and citation accuracy
  • You'll spend most of your time debugging edge cases and improving reliability
  • Ship features weekly through our CI/CD pipeline

Requirements

  • 3+ years in software engineering, 1+ year working with LLMs
  • Hands-on experience with LangChain and RAG patterns
  • Familiarity with OpenAI API and Hugging Face models
  • Strong Python skills and experience with FastAPI
  • Comfort with Docker and basic DevOps workflows

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Job Type

Full-time

Level

Mid-Level

Language

English

Salary Range

$100k – $130k / year

AI Expertise

AI & Machine Learning Engineers NLP & Prompt Engineering

Skills

python langchain openai api rag hugging face docker fastapi

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