AI Senior Engineer

Job description

**Core Responsibilities:** - Develop, maintain, and scale a RAG-based chatbot system. - Build and optimize document ingestion pipelines, including parsing, chunking, embedding, and indexing large-scale text corpora. - Orchestrate LLM workflows using tools like custom logic for context construction, prompt templating, and fallback handling. - Own the end-to-end deployment stack: API development with FastAPI, and service management on cloud VMs. - Collaborate cross-functionally to identify automation opportunities, define solution scope, and incorporate user feedback into iterative model improvement. - Contribute to internal tooling for document updates, re-indexing, and evaluation, maintaining reliability across multiple knowledge domains. **Experience:** - Industrial experience of 7-10 years - 4+years of experience in building and deploying LLM-based system **Skills & Competencies:** **Must Have:** - A Bachelors degree (or above) in any relevant field (e.g., Computer Science, Statistics) is strongly preferred. - 4+ 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).