Before bringing AI expertise into a project, it can help to define the actual technical requirement first.
Some common areas include:

Machine Learning: model development, training, and evaluation
Generative AI and LLMs: AI applications, copilots, and language-based systems
RAG: connecting language models with company-specific information
AI Agents: tool calling and multi-step workflow automation
MLOps: model deployment, monitoring, and versioning
Computer Vision: image recognition, detection, and visual analysis
NLP: classification, semantic search, and conversational applications

The required expertise can also change as an AI system moves from experimentation into production. Development teams may therefore need different technical capabilities at different stages of an AI project.

More information on AI development roles and technical requirements is available through AI Staff Augmentation Services.