Role Overview
We are looking for a skilled and versatile AI/ML Engineer with hands-on expertise across Retrieval-Augmented Generation (RAG), LangChain, LangGraph, and Optical Character Recognition (OCR). The ideal candidate will design, build, and deploy intelligent AI-powered systems that combine large language models (LLMs), document intelligence, and agentic workflows to solve real-world business problems at scale.
Key Responsibilities
● Design and implement end-to-end RAG pipelines integrating vector databases (FAISS, Pinecone, Weaviate, ChromaDB) with LLMs for accurate, grounded responses.
● Build and optimize document ingestion pipelines including chunking strategies, embedding generation, and metadata filtering.
● Develop production-ready LLM applications using LangChain's chains, agents, tools, and memory components.
● Implement conversational agents with memory management (buffer, summary, vector store memory) and multi-step reasoning.
● Architect stateful multi-agent systems using LangGraph including cyclic reasoning loops, conditional edges, and human-in-the-loop workflows.
● Design and deploy OCR pipelines for processing scanned documents, PDFs, invoices, and forms using engines like Tesseract, PaddleOCR, and EasyOCR.
● Implement document layout analysis to extract tables, headers, key-value pairs, and structured fields from unstructured documents.
● Integrate OCR outputs with downstream NLP and LLM pipelines for intelligent document processing (IDP).
● Monitor agent performance, debug hallucination issues, and implement guardrails for production deployments.
● Collaborate with product and data engineering teams to translate business requirements into scalable AI solutions.
● Document technical designs, architecture decisions, and system performance benchmarks.
Required Skills & Qualifications
● Strong hands-on experience with RAG frameworks (LlamaIndex, LangChain, Haystack) and vector databases.
● Proficiency with LangChain v0.2+ including LCEL, agents, tools, and structured output generation.
● Experience building stateful agent graphs with LangGraph including nodes, edges, and state schemas.
● Hands-on experience with OCR engines (Tesseract, PaddleOCR, EasyOCR) and cloud document AI APIs (Google Vision, AWS Textract, Azure Form Recognizer).
● Proficiency in Python with experience in async programming, REST APIs, and microservices.
● Familiarity with LLM providers such as OpenAI, Anthropic Claude, Gemini, Cohere, or Mistral.
● Experience with embedding models (OpenAI Ada, BGE, SentenceTransformers) and similarity search.
● Knowledge of image pre-processing and computer vision libraries (OpenCV, Pillow, scikit-image).
● Familiarity with cloud platforms (AWS, GCP, Azure) for model hosting, storage, and deployment.
● Understanding of prompt engineering, output parsers, and LLM evaluation techniques.
Preferred / Good to Have
● Experience with multi-modal RAG (text + image) and hybrid search (BM25 + dense retrieval).
● Knowledge of agentic patterns such as ReAct, Plan-and-Execute, Reflexion, and supervisor agents.
● Familiarity with LangSmith for tracing, debugging, and evaluating LLM applications.
● Experience with document AI models such as LayoutLM, Donut, or TrOCR.
● Exposure to Intelligent Document Processing (IDP) platforms and workflow automation tools.
● Knowledge of multi-lingual OCR and Indic script recognition.
● Contributions to open-source AI/ML or NLP projects.
Educational Qualification
● B.E. / B.Tech / M.Tech in Computer Science, Information Technology, or a related field.
● Equivalent practical experience with a strong portfolio of AI/ML projects will also be considered.
Pay: ₹1,000,000.00 - ₹1,500,000.00 per year
Benefits:
- Cell phone reimbursement
- Flexible schedule
- Health insurance
- Internet reimbursement
- Leave encashment
- Life insurance
- Provident Fund
Work Location: In person
