Data Scientist at Randstad Digital, London Area, £Contract Rate

Contract Description

AI / LLM Engineer (Copilot, Azure AI)


Leeds (Hybrid – 3 days onsite)

| Contract | Outside IR35 | Competitive Day Rate


We’re looking for a hands-on AI / LLM Engineer to design and deliver enterprise-grade Generative AI and Copilot solutions within a modern cloud environment.


This role sits at the intersection of AI engineering, architecture, and platform delivery, with a strong focus on building scalable, secure, and production-ready AI systems.


What You’ll Be Doing

  • Design, build and deploy Copilot solutions, AI agents and LLM-powered applications
  • Develop end-to-end LLM workflows (prompt orchestration, automation, integrations)
  • Implement and optimise RAG pipelines, embeddings and vector search strategies
  • Integrate AI solutions with enterprise systems, APIs and data platforms
  • Build scalable and reusable components (prompt libraries, connectors, templates)
  • Apply secure-by-design and responsible AI practices (guardrails, monitoring, auditability)
  • Implement observability and monitoring (logging, telemetry, performance tracking)
  • Troubleshoot and improve model performance, reliability and hallucination issues
  • Collaborate with cross-functional teams across engineering, architecture and governance

Key Skills & Experience

  • Proven experience building LLM / Generative AI solutions in production
  • Strong understanding of:
  • RAG (Retrieval-Augmented Generation)
  • Embeddings and vector databases
  • Prompt engineering and orchestration
  • Hands-on experience with:
  • Azure AI / Azure OpenAI
  • Copilot Studio or similar agent frameworks
  • Experience integrating with APIs and enterprise systems
  • Knowledge of secure development practices (authentication, data protection, compliance)
  • Familiarity with DevOps, CI/CD, monitoring and cloud-native architectures
  • Ability to debug AI behaviour (hallucinations, inconsistency, performance issues)

Nice to Have

  • Experience in financial services or regulated environments
  • Exposure to AI governance, risk and compliance frameworks
  • Experience with agent frameworks (e.g. orchestration tools, Semantic Kernel, LangChain)