Job Summary:

The AI Engineer will be responsible for helping identify, develop, implement and scale AI solutions across the CIMS organisation. The role will work closely with business stakeholders to understand existing processes and AI use cases, assess appropriate technology approaches, and turn promising solutions into practical, production-ready capabilities.

The role is hands-on and requires a combination of AI engineering, solution thinking and business problem-solving. The successful candidate will help move AI initiatives beyond experimentation by improving operational efficiency, scaling successful use cases and delivering measurable business value.

What You'll Be Responsible For:

Understand business processes, pain points and existing AI use cases, and identify opportunities where AI can create measurable value.
Assess existing AI solutions and pilots and recommend practical approaches to improve, integrate and scale them.
Design, develop and implement AI-enabled solutions using appropriate pro-code, low-code and enterprise-approved technologies.
Build and integrate solutions using capabilities such as Generative AI, LLMs, RAG, AI agents, automation, APIs and enterprise platforms.
Translate business requirements into practical technical solutions while balancing usability, scalability, security, data privacy and responsible AI considerations.
Work with Technology, business SMEs, AI governance and other stakeholders to take solutions from assessment and prototyping through implementation and adoption.
Create reusable solution patterns and approaches that can be applied across CIMS processes and global operations.
Measure the impact of AI solutions through metrics such as efficiency, turnaround time, quality, adoption and capacity released.
Stay current with emerging AI capabilities and recommend relevant technologies where they can address business needs effectively.

Qualifications:

Bachelor's or master's degree in computer science, engineering or a related field, or equivalent practical experience.
Typically 5 - 8 years of experience in AI engineering, software engineering, GenAI, automation or related technology roles, with hands-on delivery experience.
Hands-on experience developing or implementing AI-enabled solutions, preferably taking solutions from concept or pilot through production.
Strong understanding of Generative AI, LLM applications, prompt engineering, RAG, AI agents and/or intelligent automation.
Experience with Python and/or other relevant programming technologies, APIs and enterprise application integration.
Ability to understand ambiguous business problems, evaluate technology options and translate them into practical solutions.
Strong communication and stakeholder-management skills, with the ability to work effectively with both technical and non-technical stakeholders.

Preferred Experience:

Experience in insurance, financial services or another regulated environment.
Experience working with Microsoft AI and automation technologies such as Azure AI, Copilot Studio and Power Platform.
Experience integrating AI with business applications, data sources, document repositories or workflow platforms.
Experience taking AI pilots into production and scaling solutions across teams, processes or geographies.

What's in it for me

You will have the opportunity to work on practical AI use cases within a global organisation, helping move AI capabilities from experimentation to scalable business solutions. WTW also provides opportunities for global collaboration, AI upskilling and professional development.

Artificial Intelligence Engineer