Under the supervision of the UNICEF ICT Division (ICTD) lead, the consultant will continue the development of UniBot and perform the following activities:

1. Application Architecture Development:

?Develop and add features to GenAI solution that leverages Microsoft Azure AI services such as Azure AI Studio, Azure Cognitive Search, Prompt Flow, etc. integrated with OpenAI’s LLMs such as GPT4 and the data sources mentioned above. Similar experience with Google Vertex or AWS Sage a plus.

?Suggest opensource options if any.

2.Data Management:

?Develop and maintain data pipelines for handling a high volume of structured and unstructured documents uploaded by a user, such as:

o Upload files and folders

o SharePoint integration and content transformation

o Web scraper

?Ensure data security and compliance with relevant UNICEF data protection regulations.

3.User Administration

?Implement roles and users’ groups using Microsoft Entra ID

Create basic UI for users’ administration.

4. User Interface Development:

?Build a simple, user-friendly UI/UX for UNICEF staff members to upload documents and interact with the GenAI.

?Implement features to automate document upload and chat-based querying.

5.Cost Tracking

?Implement a feature to track and display the cost associated with chat interactions.

?Implement a feature to track backend transactions.

?Implement basic reports with options for duration, frontend and/or backend transactions.

6.Logs, Usage Reports and History

?Log timestamped training events, algorithm change events, prompts, responses, user assessment (thumbs up/down, hallucination, bias, accuracy)

?Implement Provide method(s) to manage log size, backups and archival.

?Create basic usage reports and guidance for PowerBI users.

?Provide users with access to chat history for reference and review.

?Provide the ability to reset the session/start new session.

7.Prompt Engineering and Model Fine tuning:

?Document efficient prompt examples that help the LLMs generate accurate and relevant responses.

?Document the best ways to train and fine-tune LLMs for domain-specific knowledge and applications.

?Employ RAG, Prompt or other techniques to anchor the GenAI responses to the provided data sources and establish techniques to mitigate hallucinations and increase accuracy.

8.Security and Compliance:

?Ensure compliance with UNICEF security, ethics, and privacy standards.

9.Testing and Deployment:

?Conduct thorough testing of the chatbot for functionality, accuracy, and security.

?Deploy the solution on UNICEF’s Azure.

?Develop a quality plan template for testing validating and revalidating the solution.

10.Documentation and handoff

?Document the work and application in a simple and detailed manner.

?Provide documentation and basic training for end-users and administrators

Requirements: 

Education Qualification

• An advanced university degree (Master’s or higher) in Computer Science, Data Science, Mathematics, AI and/or other quantitative field.
  Certifications in Azure AI, AWS Sage Maker, or Google Vertex AI.
• Certification in data science.

Knowledge/Expertise/Skills required

• A minimum of 5 years of relevant professional experience in building AI solutions.
• Proven experience in Retrieval Augment Generation (RAG) in a cloud computing environment
• 5 years’ experience preferably with Microsoft Azure AI infrastructure, or Google Vertex AI, and AWS Sage Maker.
• Proficient in creating data pipelines and managing large datasets.
• Experience in prompt engineering and implementing AI security measures.
• Knowledge of basic UI/UX design principles. Knowledge in accessibility a plus.
• Excellent problem-solving and communication skills.
• Fluency in English is required. Knowledge of another official UN language (Arabic, Chinese, French, Russian or Spanish) is an asset.