IT & Software

Backend Software Engineer Python LLM - Finance

Client Server

London · Greater London · United Kingdom

Overview

In this Backend Software Engineer role you will design and build autonomous AI systems that incorporate multi-modal LLMs, enabling agentic workflows and data-driven interactions. You’ll optimise and deploy large language and multimodal models with a focus on performance, while building scalable MLOps pipelines and supporting production-ready applications. You’ll guide cross-functional teams and clients in GenAI adoption, contributing to scalable AI deployments in a金融 technology consultancy context. This is a hands-on, impact-driven opportunity with a focus on real-world AI delivery.

Pay / Benefits
  • pension
  • Life Assurance
  • Income Protection
  • Private medical care for you and your family
  • Travel Insurance
  • Charitable giving","Gym membership for you and your family","Flexible holiday scheme
Responsibilities
  • Design and develop autonomous AI systems with multi-modal LLMs (text, image, audio, video)
  • Create agentic workflows enabling AI agents to interact with data sources and APIs using prompt engineering and RAG
  • Optimize and deploy LLMs and multimodal models emphasizing performance and latency
  • Build scalable MLOps pipelines and full-stack applications for production-grade AI deployments
  • Provide consultative guidance to multidisciplinary teams and clients on AI engineering and GenAI adoption
Key requirements
  • Bachelor in Computer Science or related STEM
  • strong Python software engineering background including API development
  • hands-on experience deploying LLMs and multimodal models at scale in production
  • strong understanding of scalable MLOps, observability, and cloud-native AI deployment
  • collaborative and pragmatic with advanced stakeholder communication, problem-solving and Agile project management skills in Agile environments
  • collaborative
  • pragmatic
  • stakeholder communication
  • Python
  • API development
  • deploying LLMs and multi-modal models at scale

Reference: WJ-747_30169706

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