AI Engineer

The AI Consultant should be able to bridge the gap between technical implementation and business alignment. Should be able to

guide team through the early stages of AI adoption. The primary focus of this role is to:

i. Establish foundational AI capabilities

ii. Define and promote best practices

iii. Develop and implement a structured AI framework

iv. Promote consistency, scalability, and compliance.

Key accountabilities / milestones & outcomes:

• Detailed instructions on how to craft effective prompts for AI tools, including examples of simple and instructional prompts.

• Prompt Optimisation: Tips for ensuring accurate and relevant responses from AI platforms. Guidelines for structuring queries to

get the most relevant results and verifying the accuracy of AI-generated outputs

• Model selection criteria – matrix to help select the most appropriate model based on use case.

• Prompt Templates - Templates for documenting prompt flows, auditing etc.

• Prompt Libraries - Curated collections of effective prompts for different domains

• Prompt Testing Interface – how to test prompts against different models including side by side comparison.

• Model behaviour insights - Temperature and token limit effects

• Define a process to Integrate lifecycle management for models, including versioning, retraining, and retirement. Consider use of

GIT Hub.

• Aligning with client’s Responsible AI Policy.

• Recommendations on how best to embed KPIs and success metrics for AI initiatives, and benefit tracking mechanisms to measure

impact and value delivery.