RAG AI Developer (LLM + Retrieval) – EdTech
AP Guru
2 - 5 years
Mumbai
Posted: 12/02/2026
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Job Description
Job Summary:
We are looking for a RAG (Retrieval-Augmented Generation) AI Developer to build and improve AI features for our EdTech productssuch 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
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