Software Engineer, Generative AI (uk)

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

Software Engineer, Generative AI role focused on building secure, scalable generative AI services and applications, including high-performance APIs and microservices for integrating LLMs and agentic workflows. The role involves system design, owning architecture, and partnering with DevOps for CI/CD, logging, and monitoring. Requires strong Python, generative AI, LLM, vector database, and microservices experience, with exposure to cloud platforms and enterprise architecture.

What you'd actually do

  1. Design and develop robust, secure, and scalable 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 to integrate advanced AI models and sophisticated agentic workflows into our core platform
  3. Act as a whole-systems thinker by making meaningful system design decisions and owning the architecture of core platform components from initial proposal through production deployment
  4. Implement and maintain responsive user interfaces using technologies like React and TypeScript to deliver intuitive user experiences and bridge the gap between backend services and frontend enablement
  5. Drive proactivity without red tape by clearly communicating changes, plans, and proposals to cross-functional teams and collaborating closely with product managers, data scientists, and DevOps engineers
  6. Partner with DevOps teams to build continuous deployment, logging, and monitoring systems that ensure top-tier performance, security, and reliability across distributed workloads

Skills

Required

  • 3-5+ years of hands-on experience as a software engineer
  • Python development in production environments
  • building and deploying generative AI applications
  • leveraging LLMs
  • vector databases like Pinecone, Weaviate, or pgvector
  • modern open-source agentic frameworks
  • microservices architecture
  • RESTful APIs
  • cloud platforms such as AWS, GCP, or Azure
  • containerization with Docker and Kubernetes
  • FastAPI
  • Asyncio
  • database systems like PostgreSQL
  • AI developer tooling like Claude, Cursor, or GitHub Copilot
  • enterprise architecture
  • IAM, SSO, SAML, OAuth, OIDC, RBAC
  • robust security best practices
  • building services for enterprise administration and billing systems

Nice to have

  • React
  • TypeScript

What the JD emphasized

  • strong emphasis on Python development in production environments
  • Proven expertise in building and deploying generative AI applications
  • Practical experience with microservices architecture
  • solid grasp of modern web technologies
  • Exposure to enterprise architecture
  • mentor other engineers

Other signals

  • building and deploying AI agents
  • enterprise-grade LLMs
  • generative AI solutions
  • AI adoption