Senior Agentic AI Engineer/AI Architect at UST, London, 6 Months, £Contract Rate

Role description

Senior Agentic AI Engineer / AI Architect - multi-agent AI systems

London (4 Days Onsite)
6 month Contract (Inside IR35)

UST is seeking a Senior Agentic AI Engineer / Architect to design, build, and deploy enterprise-scale AI solutions powered by LLMs, Agentic AI, and Multi-Agent Systems.

This is a hands-on role for someone who has moved beyond PoCs and has successfully delivered production-grade AI applications at scale. You'll work closely with architects, engineers, and business stakeholders to solve complex challenges using the latest AI technologies.

What You'll Do

• Design and develop multi-agent AI systems using modern orchestration frameworks.
• Build intelligent workflows leveraging agent planning, reasoning, memory, tool usage, and task delegation.
• Deliver production-ready solutions using LLMs, RAG, and AI-powered automation.
• Develop secure, scalable Python services, APIs, and orchestration layers.
• Architect and optimise retrieval pipelines, vector search, embeddings, and knowledge systems.
• Implement AI observability, evaluation, guardrails, monitoring, and governance.
• Deploy and operate cloud-native solutions on AWS.

What We're Looking For:

• Proven experience building and deploying production-grade Generative AI or Agentic AI solutions.
• Strong Python software engineering and backend development expertise.
• Hands-on experience with multi-agent architectures and agent orchestration.
• Experience with frameworks such as:
  • LangGraph
  • CrewAI
  • AutoGen
  • Semantic Kernel
  • OpenAI Agents SDK
  • LlamaIndex
• Strong knowledge of:
  • LLMs and Prompt Engineering
  • RAG architectures
  • Vector Databases and Embeddings
  • APIs, Microservices, and Event-Driven Architectures
• Experience deploying enterprise AI solutions within AWS environments.

Highly Desirable:

• Experience architecting AI platforms at enterprise scale.
• Knowledge of AI evaluation frameworks, observability, and governance.
• Experience leading technical design and mentoring engineering teams.
• Exposure to Kubernetes, Docker, and MLOps practices.