Minimum of Bachelor's Degree in Computer Science, Computer Engineering, Machine Learning / Data Science / AI or related disciplines
Able to understand and apply a range of AI/ML techniques for regression and classification
Familiar with popular python packages ( e.g. pandas, matplotlib, scikit-learn, XGBoost, NLTK, spaCy )
Understanding of LLM concepts (e.g. context windows, embeddings, chunking, token management) and architectures (e.g. RAG)
Experience with context engineering techniques and prompt optimization strategies
Proficient in git, SQL
Proficient in Business Intelligence tools (e.g. Tableau, Qlik, MS PowerBI, Microstrategy)
Bonus skillsets:
Proficient in modern programming languages (e.g. typescript, C#)
Experience in cloud platform and services preferably in AWS
Experience in Docker/Kubernetes
Experience with web frameworks and full-stack development, including backend frameworks (e.g. FastAPI, Flask, Express.js) and RESTful API development, and frontend technologies (e.g. React, Vue.js, HTML/CSS, TypeScript)
Experience with LLM frameworks (e.g. LangChain, LlamaIndex, Hugging Face Transformers)
Knowledge of vector databases and embedding techniques (e.g. Pinecone, Chroma, FAISS)
Understanding of AI agent frameworks and multi-agent systems
Strong presentation skills and ability to explain technical concepts clearly to a non-technical audience
Proficient in statistical software tools (e.g. R, SAS)
