Overview
Support research and development of Agentic AI, including autonomous agents, multi-agent systems, and Large Language Models (LLMs), to address global development challenges.
Key Responsibilities
- Assist in conducting research on Agentic AI applications for development challenges.
- Support drafting analytical briefs on project findings and methodologies.
- Support development, implementation, and testing of Agentic AI solutions.
- Support development and optimization of multi-agent workflows.
- Assist in building proof-of-concept agentic systems.
- Assist in building tools, APIs, and data connectors for agent interaction.
- Support implementation of Retrieval-Augmented Generation (RAG) systems.
- Provide support to the Technical Specialist as required.
Required Experience
- Proficiency in Python programming for building agent workflows, working with APIs, and developing applications.
- Strong knowledge of prompt engineering for LLM-based applications and agent behaviors.
- Experience implementing agentic AI systems using frameworks such as LangChain, LangGraph, CrewAI, AutoGen, or Semantic Kernel.
- Familiarity with open- and closed-source LLMs (e.g., OpenAI GPT, Claude, Gemini, LLaMA).
- Exposure to Retrieval-Augmented Generation (RAG) systems and vector databases (e.g., ChromaDB, Pinecone, Weaviate, Milvus).
- Knowledge of evaluation frameworks for agentic AI systems.
- Experience with Microsoft Copilot Studio, Power Automate, or other Microsoft Power Platform tools, or an interest in workflow automation and Microsoft 365 integration.
Qualifications
- Enrolled in a second university degree programme (Master’s Degree).
- Enrolled in the final academic year of a first university degree programme (Bachelor’s Degree).
- Graduated with a university degree in fields such as Computer Engineering, Computer Science, Statistics, Econometrics, Mathematics, Economics or similar.
