Job Description

We are looking for an AI Governance & Risk Analyst to support AI policy implementation, risk assessments, and governance activities across AI use cases. You will help define guardrails, support reviews, and improve oversight for AI systems and related vendors.
Client:
Our client is one of the largest online retailers worldwide, generating annual revenue exceeding £2 billion. Headquartered in the UK, they are focused on revolutionizing grocery e-commerce worldwide. Their custom-built solutions are designed to meet the complex and evolving needs of shoppers while enhancing productivity, flexibility, and profitability for grocery retailers online.
Project Overview:
This project supports the safe and practical adoption of AI capabilities within a logistics focused platform. You will help close governance gaps, guide risk tiering, and support controls for AI solutions throughout their lifecycle.

Responsibilities:
  • Turn AI policies into practical local standards
  • Fill policy gaps for agents, non human identities, and Superblocks with lightweight guardrails
  • Run AI use case intake and risk tiering
  • Guide DPIAs and vendor reviews
  • Set agent boundaries for read and write scopes and human in the loop controls
  • Define RAG data access tiers
  • Check audit logging and the impact of vendor model updates
  • Support AI solution lifecycle and decommissioning activities
Required Qualifications:
  • Experience with 2 to 4 years in IT risk, data governance, or information security compliance
  • Experience working in a matrixed organization
  • Understanding of GenAI basics
  • Ability to work with stakeholders across multiple teams
Nice To Have:
  • Experience with UK or EU DPIAs
  • Experience with GCP governance
  • Experience in logistics environments
Note:

✨ Our intelligent job search engine discovered this job and republished it for your convenience.
Please be aware that the job information may be incorrect or incomplete. The job announcement remains the property of its original publisher. To view the original job and its full details, please visit the job's URL on the owner’s page.