Jobin Jose
Software Engineer @NeST Digital
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WORK HISTORY
Software Engineer @NeST Digital
Ernakulam, IN
Developed scalable backend systems and event-driven data pipelines using Python, AWS Lambda, Amazon SQS, S3, and PostgreSQL, enabling efficient processing and centralized access to large-scale statistical filing data through FastAPI-based REST and GraphQL services. Modeled highly connected insurance datasets using Amazon Neptune graph databases, and built AI-powered chatbot solutions using Amazon QuickSuite by developing custom MCP tools and integrating to quick suite through AWS Bedrock Core Agent to extract and query complex graph data, integrating GenAI techniques to validate response accuracy and ensure reliable, context-aware outputs.• Built AI-driven automation systems including GenAI-powered email responders and intelligent chatbot platforms using LLMs and Retrieval-Augmented Generation (RAG). Implemented RASA NLU for intent classification and routing, reducing unnecessary LLM invocations by ~25%, lowering operational costs and improving response latency and system throughput while delivering context-aware responses from internal knowledge bases.• Developed NLP classification models and AI-powered data processing pipelines using SimpleTransformers and neural network architectures, strengthening machine learning capabilities for document and dataset analysis.• Contributed to enterprise-scale backend platforms using Java and Spring, implementing system enhancements for regulatory data validation and reporting workflows, improving reliability and compliance in statistical insurance data processing systems.
EDUCATION
MANGALAM COLLEGE OF ENGINEERING
BTECH, COMPUTER SCIENCE AND ENGINEERING
ABOUT JOBIN JOSE
Software Engineer focused on building scalable backend systems and AI-driven applications, with strong emphasis on system architecture, distributed systems, and production-grade AI integration.🤖 Experienced in developing LLM-powered systems, intelligent automation platforms, and high-performance APIs, designed for reliability, scalability, and real-world deployment. Strong background in backend engineering and cloud-native architectures, leveraging Python-based frameworks, AI/ML technologies, and AWS cloud infrastructure to build resilient, scalable platforms. Committed to empowering productivity through deep understanding of core engineering concepts combined with AI-driven automation, enabling significant improvements in development speed, system efficiency, and solution quality.🧠 Core Expertise🤖 Generative AI • 🧩 Large Language Models (LLMs) • n8n Workflow Automation • AI System Design • Scalable Backend Architecture • Distributed Systems • Cloud-Native Systems • AWS • High-Performance APIs Technical Stack Python • FastAPI • REST APIs • 🧠 AI/ML Frameworks • RAG Systems • Backend Microservices • Cloud Infrastructure Focus Areas🤖 AI-powered applications • 🧠 LLM systems • scalable backend platforms • AI microservices • cloud-based architectures
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