6+ years of hands-on experience in AI/ML engineering, with real-world deployment of models and pipelines.
Strong expertise in Python
Proven experience building and deploying LLM-based systems, particularly those using retrieval-augmented generation (RAG).
Solid understanding of vector databases, embeddings, and semantic search architecture.
Strong skills in data engineering: ETL pipelines, data cleaning, transformation, and large-scale processing.
Experience in building REST APIs, containerizing services with Docker, and deploying to cloud infrastructure (preferably Azure or AWS).
Strong understanding of cloud platforms and modern data architectures (e.g., AWS, GCP, Azure).