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Generative AI & LLM

- Design and develop LLM-powered applications for enterprise use cases.
- Build production-grade Retrieval-Augmented Generation (RAG) pipelines, including data ingestion, chunking, embeddings, retrieval, re-ranking, and response generation.
- Develop AI agents and agentic workflows to automate multi-step business processes.
- Implement tool/function calling and structured LLM workflows.
- Work with multiple LLM providers and models based on business and technical requirements.
- Perform prompt engineering, context optimization, and response evaluation to enhance model performance.
- Continuously improve AI accuracy, reliability, scalability, and performance.
- Lead architecture decisions for Generative AI solutions and establish engineering best practices.

Document & Knowledge Intelligence

- Build intelligent solutions for processing, analyzing, and understanding large volumes of enterprise documents.
- Develop document ingestion, classification, information extraction, and semantic search capabilities.
- Implement evidence-based response generation with source references and citations.
- Develop document comparison, validation, and information extraction workflows.
- Work with both structured and unstructured data sources to deliver business insights.

Full-Stack Engineering

- Develop scalable backend services using TypeScript and Node.js.
- Build and maintain REST APIs and integrations with enterprise systems.




- Develop contemporary frontend applications using React and Next.js.
- Design, optimize, and maintain PostgreSQL databases.
- Work with vector databases and semantic search technologies to support AI-driven applications.
- Implement authentication, authorization, and role-based access control (RBAC) mechanisms.
- Develop reusable, maintainable, and scalable application components.
- Drive architectural improvements and support technology evaluation and selection.

AI Automation & Integrations

- Integrate LLMs and AI capabilities into existing enterprise applications.
- Build automated workflows connecting AI models with APIs, databases, and external services.
- Design and implement reliable human-in-the-loop workflows where business validation is required.
- Develop monitoring, logging, and error-handling frameworks for AI-powered solutions.
- Ensure the reliability, scalability, and maintainability of AI automation processes.

Leadership & Mentoring

- Mentor junior developers and engineers on AI engineering principles and best practices.
- Conduct code reviews and promote high-quality engineering standards.
- Collaborate with cross-functional teams to define technical strategy and solution architecture.
- Contribute to innovation initiatives and drive the adoption of emerging AI technologies across the organization.

Duties:

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📌 AI Software Engineer (Chennai)
🏢 Quinte Financial Technologies
📍 Chennai