Roles & Responsibilities

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Design and develop intelligent AI-based applications using advanced NLP and LLM techniques to solve real-world business challenges in financial services.

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Build and optimize Retrieval-Augmented Generation (RAG) pipelines leveraging structured and unstructured financial data.

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Integrate and orchestrate LLMs/SLMs for question-answering, summarization, semantic search, and document understanding.

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Develop and maintain RESTful APIs (sync and async) to serve NLP models and chatbot interfaces using frameworks like FastAPI, Flask, etc.

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Should have knowledge of advanced prompting techniques.

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Implement semantic search, hybrid search, and text retrieval systems using Elasticsearch and vector databases (e.g., FAISS, Pinecone, Weaviate).

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Perform NLP tasks such as entity recognition, text classification, intent detection, embedding generation, and sentiment analysis where required.

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Monitor and fine-tune LLM/SLM performance with real-world user data to improve relevance, latency,



and accuracy.

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Exposure to LLMOps tools for monitoring, evaluation, and versioning of AI models in production.

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Build, train, and evaluate deep learning models for NLP tasks including classification, NER, summarization, and embedding generation.

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Develop traditional machine learning models (e.g., regression, decision trees, clustering) for structured data analysis and prediction tasks.

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Interact with cross-functional teams to understand system issues and follow up with respective teams to get them fixed.

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Understand and identify areas of improvement across businesses and participate in solution identification and implementation.

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Should be able to work as an Individual Contributor on current and existing projects.

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Positive and problem-solving attitude, must work as an independent contributor.

📌 Senior Solution Architect – Google Cloud (Bengaluru)
🏢 CGvak Software Exports
📍 Bengaluru