RAG AI Developer (LLM + Retrieval) – EdTech

Job Summary:
We are looking for a RAG (Retrieval-Augmented Generation) AI Developer to build and improve AI features for our EdTech products—such as course Q&A bots, tutor assistants, content search, and internal knowledge assistants. You will work on document ingestion, embeddings, retrieval pipelines, evaluation, and deployment.
Key Responsibilities:
Build and maintain RAG pipelines: ingestion → chunking → embedding → vector storage → retrieval → generation.
Implement hybrid search (semantic + keyword), reranking, filters, and metadata-based retrieval.
Integrate LLMs with tools/frameworks (e.g., LangChain / LlamaIndex or custom pipelines).
Work with vector databases (e.g., Pinecone, Weaviate, FAISS, Chroma, Milvus) and optimize retrieval performance.
Create evaluation metrics for RAG quality (faithfulness, relevance, context precision/recall) and reduce hallucinations.
Build prompt templates, guardrails, and citation-based answers.
Deploy services/APIs (FastAPI/Flask), monitor latency/cost, and implement caching strategies.
Collaborate with product/content teams to define data sources and user workflows.
Required Skills & Qualifications:
1+ year experience building NLP/LLM features (must have some hands-on RAG or retrieval work).
Strong Python skills.
Experience with embeddings, chunking strategies, and document loaders (PDF/HTML/Doc).
Familiarity with at least one vector DB and retrieval methods (cosine similarity, MMR, etc.).
Understanding of basic ML concepts and text preprocessing.
Preferred (Nice to Have):
Experience with OpenAI / Anthropic / Google / open-source LLMs (Llama, Mistral, etc.).
Experience with OCR pipelines (for scanned PDFs), speech/text, or multilingual content (helpful for EdTech).
Experience with Docker, cloud deployment (AWS/GCP/Azure), CI/CD.
Prior work on chatbots, tutoring systems, or knowledge bases.
What Success Looks Like (KPIs):
Higher answer accuracy + lower hallucination rate
Faster retrieval latency and lower compute cost
Clear citations and better user satisfaction on Q&A flows
Location: On-site – Girgaon , Mumbai
Experience: 1+ year (hands-on)
Job Type: Full-time

Work arrangement
No