Responsibilities:- Build and maintain web applications, APIs, and services using Python.- Develop and improve AI applications using large language models (LLMs), including Retrieval-Augmented Generation (RAG) solutions.- Design document-ingestion, chunking, embedding, retrieval, and response-generation workflows.- Design and develop tools for AI applications, including function-calling workflows and integrations using the Model Context Protocol (MCP).- Integrate vector databases and search technologies into production systems.- Develop responsive frontend features and connect them to backend APIs.- Evaluate AI output quality, retrieval relevance, latency, and cost; improve performance and reliability.- Implement authentication, authorization, logging, testing, and monitoring.- Apply software engineering best practices, including SOLID principles and design patterns, to build scalable, maintainable systems.- Deploy and operate LLMs in on-premises environments using inference servers such as vLLM or SGLang.- Collaborate with product, design, and engineering teams to turn requirements into production-ready features.- Document technical decisions and contribute to code reviews and engineering standards.Required Qualifications:- Professional experience developing full-stack web applications.- Strong Python skills and experience with frameworks such as FastAPI, Django,



or Flask.- Experience designing and building REST APIs or similar service interfaces.- Hands-on experience developing LLM-powered applications and RAG workflows.- Familiarity with function calling, MCP, and designing or developing tools for AI applications.- Familiarity with embeddings, vector search, prompt design, and document-processing pipelines.- Experience with a relational database such as PostgreSQL and at least one vector database or vector-search solution.- Frontend experience with JavaScript or TypeScript and a up-to-date framework such as React.- Familiarity with Git, automated testing, deployment workflows, and software engineering best practices.- Strong problem-solving, communication, and collaboration skills.Preferred Qualifications:- Experience with cloud platforms such as AWS, Azure, or Google Cloud.- Familiarity with Docker, CI/CD, and production observability.- Experience deploying LLMs on-premises, including using inference servers such as vLLM or SGLang.- Experience with LLM evaluation, guardrails, hybrid search, reranking, or agentic workflows.- Experience handling sensitive data and implementing security and privacy controls.- Contributions to technical projects, open-source software, or developer communities. (ref:hirist.tech)

📌 Hind Industec - Full Stack AI Engineer (Pune)
🏢 Hind Industec
📍 Pune