GenAI Architect: LLM & RAG Systems Lead

Primary

Skills:

(
AI Data Scientist
)

• Deep Expertise in the following:
  • Large Language Models (LLMs) and Multimodels
  • Foundation Model Architectures (Transformers, Encoder/Decoder)
  • API integration from providers like (e.g., OpenAI, Cohere).
  • Model tuning pipeline development
  • Prompt engineering
  • Reinforcement learning from human feedback (RLHF).
  • Frameworks :
    PyTorch, Tensor Flow,Lang Chain, Llama Index
  • Strong programming skills in Python, and experience with data engineering workflows (Spark, Airflow, SQL).
• Hands on experience in
  • Fine-tuning & Prompt Engineering (LoRA, PEFT)
  • Retrieval-Augmented Generation (RAG) pipelines
  • Python:
    Num Py, Pandas, Scikit-learn, Hugging Face, OpenAI API
• Knowledge of AI ethics, explainability, and governance in generative models

• Experience with vector databases (e.g., FAISS, Weaviate, Pinecone) and scalable RAG systems
• Familiarity with GPU compute infrastructure and distributed model training
• MLOps for LLMs:
  Deployment, Monitoring, Versioning
• Classical Machine learning like Supervised Learning, UnSupervised learning models