Software Engineer, Generative AI (uk)

Writer Writer · AI Frontier · London, United Kingdom · Engineering, product & design

Software engineer focused on building and deploying generative AI services and applications, including agentic workflows and LLM integrations, for enterprise clients. The role involves developing scalable APIs, optimizing performance, and collaborating across teams to deliver AI solutions.

What you'd actually do

  1. Design and develop robust, scalable, and secure generative AI services and applications using Python and modern frameworks to drive enterprise-wide transformation
  2. Build and optimize high-performance, low-latency APIs and microservices for integrating advanced AI models and agentic workflows into our platform
  3. Collaborate closely with product managers, data scientists, and cross-functional engineering teams to translate complex business needs into innovative AI solutions, from concept to production
  4. Implement and maintain responsive user interfaces (primarily focused on backend enablement though some frontend interaction is expected) using technologies like React and TypeScript to deliver intuitive user experiences
  5. Partner with DevOps teams building continuous deployment, logging and monitoring; ensuring top-tier performance and reliability

Skills

Required

  • Python development in production environments
  • Building and deploying generative AI applications
  • Leveraging LLMs
  • Vector databases (e.g., Pinecone, Weaviate, pgvector)
  • Modern open source agentic Frameworks
  • Microservices architecture
  • RESTful APIs
  • Cloud platforms (AWS, GCP, or Azure)
  • Containerization with Docker and Kubernetes
  • FastAPI
  • Asyncio
  • Database systems like PostgreSQL

Nice to have

  • React
  • TypeScript

What the JD emphasized

  • 3+ years of hands-on experience as a software engineer, with a strong emphasis on Python development in production environments
  • Proven expertise in building and deploying generative AI applications, leveraging LLMs, vector databases (e.g., Pinecone, Weaviate, pgvector), and modern open source agentic Frameworks
  • Deep understanding and practical experience with microservices architecture, RESTful APIs, and cloud platforms such as AWS, GCP, or Azure, including containerization with Docker and Kubernetes

Other signals

  • building and deploying AI agents
  • enterprise-grade LLMs
  • generative AI technologies
  • sophisticated agentic workflows