AI Engineer Python Fullstack

Robert Walters
Full-timeMid
£70K - £90K/yr

AI Tools

AutoGenCrewAILangChainLangGraphLlamaLlamaIndexMistralOpenAI GPT

Tech Stack

PythonLangChainLlamaIndexAutoGenCrewAILangGraphRAGPineconeWeaviateFAISSMLflowKubeflowDockerKubernetesAWSAzureGCP

Agent Workflow

Designing RAG pipelines, LLM-powered applications, and intelligent agent architectures. Engineering GenAI, Agentic AI systems for production with autonomous agents and reasoning engines.

About the Role

We are looking for an AI Engineer to develop end-to-end AI solutions, combining modern software engineering with advanced machine learning and generative AI capabilities. You'll contribute to a global technology organization delivering large-scale digital and AI transformation initiatives for enterprise clients.

Location: London, UK (hybrid, 1-3 days onsite)
Salary: £70,000-£90,000 + bonus + benefits
Type: Permanent, Full-time
Posted: March 13, 2026 (valid through April 24, 2026)

Responsibilities:

  • Construct and implement full-stack AI applications including APIs, services, and user interfaces
  • Engineer GenAI, Agentic AI, and machine learning systems for production environments
  • Design RAG pipelines, LLM-powered applications, and intelligent agent architectures
  • Integrate AI solutions with enterprise platforms and cloud infrastructure
  • Partner with data scientists, engineers, and business stakeholders on product delivery
  • Establish technical standards and innovation practices for AI engineering

Required Skills & Experience:

  • Proficient Python development with AI/ML/NLP libraries (Hugging Face, spaCy, NLTK)
  • Hands-on experience building applications with LLMs (GPT, Llama, Mistral, Claude)
  • Framework expertise: LangChain, LlamaIndex, AutoGen, CrewAI, LangGraph
  • RAG architecture implementation with vector databases (Pinecone, Weaviate, FAISS)
  • MLOps/LLMOps proficiency (MLflow, Kubeflow, Docker, Kubernetes)
  • Cloud platform experience (AWS, Azure, or GCP)
  • Knowledge of autonomous agents, reasoning engines, and knowledge graphs

Hybrid: 1-3 days onsite in London.

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