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AI Engineer (Manager level)

Posted February 27, 2026
Full-time Mid-Senior Level

Job Overview

The role

 

This role is a key contributor in the Data & Analytics, AI team:

  • The daily work primarily focuses on  Natural Language processing (NLP).
  • This role will lead a range of data analytics efforts, including monitoring and improving the performance of our Natural Language Understanding (NLU) models
  • Collaborate with legal technology advisors, business departments, innovation lab, finance team and work in the data science lab
  • Further develop Clifford Chance's generative AI solutions

 

Who you will work with

The candidate's primary role is to develop and deliver applications for internal organisation and service-based use. It will involve collaborating with other IT teams, internal product development teams and Data & Analytics, AI team members for the architectural design and implementation of these applications. The candidate will be actively involved not only in application design but also in the realisation of those designs as applications for the cloud.

 

What you will be responsible for

 

  • Develop products as both on-premises and cloud-based applications in Python, whilst ensuring they align to Application, Enterprise, Security architecture as well as the whole-of-Government policies and framework
  • Collaborate on creating architectural designs for on-premises and cloud-based applications, including relevant documentation to effectively explain architectural design concepts and solutions to various level of stakeholders
  • Recommend new software development methodologies, design patterns and approaches to continually improve product delivery as part of the Legal Technology Solutions
  • Apply knowledge of Agile software development and DevOps to ensure best delivery of applications, ensuring focus is always kept on maintainability and scalability.
  • Identify potential and emerging technologies relevant to innovation for the Data Science Lab and wider Legal Technology Solutions group
  • Contribute to the execution of data science use cases on a need basis 

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