Overview

We are seeking a hands-on AI Engineer to serve as the primary technical contributor within a fast-moving, low-overhead setup. You will be responsible for the full lifecycle of AI development – from data validation and backend Python engineering to lightweight frontend prototyping and Azure-based deployment. This role requires a “multiple hats” approach, balancing rapid MVP development with the rigors of production-grade observability and data compliance. Client: A world-renowned higher education institution based in London, recognized as a leader in global business education. The organization is currently expanding its dedicated AI Lab to drive digital transformation and innovation across its academic and administrative functions. Project Overview: The AI Lab operates as an experimentation-first environment focused on rapidly developing, validating, and shipping AI-powered solutions. The project involves building greenfield AI agents and RAG-based tools for up to 2,000 internal users, as well as scaling an existing course recommendation engine through deep database integration and pipeline optimization.

Responsibilities:
  • AI Development & Iteration: Design and build AI agents (OpenAI, Anthropic) and RAG architectures; lead hypothesis-driven development cycles to move from MVP to production based on stakeholder feedback.
  • System Extension: Enhance an existing course recommendation agent by integrating internal databases and improving underlying data pipelines for better coverage and quality.
  • Observability & Debugging: Instrument AI flows using LangFuse to monitor agent behavior, conduct prompt evaluations, and resolve latency or logic issues.
  • Data Validation: Critically assess stakeholder datasets for reliability and GDPR compliance; communicate technical limitations of data to non-technical partners.
  • UI Prototyping: Build functional, lightweight frontends using AI-assisted workflows (e.g., Lovable, Figma) to surface tools to end-users.
  • Infrastructure Management: Deploy and maintain solutions within a pre-configured Azure environment, utilizing CI/CD pipelines and following established environment management practices.
  • Stakeholder Engagement: Collaborate directly with product and academic stakeholders to translate loosely defined needs into technical requirements and buildable solutions.
Required Qualifications:
  • 4+ years of experience in backend or full-stack development with a focus on production AI/ML systems using Python.
  • Proven track record building AI agents and deploying RAG architectures using OpenAI or Anthropic APIs.
  • Experience with LangFuse or similar tracing tools for LLM pipeline monitoring and prompt engineering.
  • Hands-on experience deploying solutions on Microsoft Azure (Azure OpenAI, App Services) and familiarity with CI/CD and Terraform.
  • Ability to analyze and critique datasets and forecast infrastructure/API run costs.
  • Solid understanding of GDPR and data privacy within an enterprise or institutional context.
  • Ability to operate as a solo technical lead and explain complex trade-offs to non-technical stakeholders.
Nice To Have:
  • Experience within the EdTech or higher education sector.
  • Background in consultancy or client-facing technical roles.
  • Specific experience with recommendation systems or personalization engines.
  • Exposure to "lab-style" or hypothesis-driven product development environments.
Note:

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