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Tier-1 brand, metro location, popular fullstack title, and broad AI requirements increase applicant competition.
Deep LLM, RAG, and AI-specific requirements create high domain bias limiting cross-industry fit.
Extensive mandatory technical stack and managerial level make hiring filters stringent and selective.
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Design, develop, deploy, and maintain AI-powered full stack applications including frontend, backend, cloud infrastructure, and AI integrations.
Build and optimize scalable codebases focusing on AI-driven features such as LLM integration, AI-generated image/video/text applications, and real-time communication via REST APIs and WebSockets.
Implement testing, CI/CD pipelines, and deployment automation ensuring performance optimization and secure authentication/authorization flows.
Strong experience in Python and FastAPI, React, SQL and NoSQL databases, and Alembic database migrations.
Proficiency with REST APIs, WebSocket communication, API testing tools, unit and integration testing, and CI/CD pipelines.
Experience integrating large language models and AI services (OpenAI, Anthropic, Gemini, etc.) and knowledge of prompt engineering and AI application development.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced full stack engineer with deep expertise in AI-powered application development and integration of LLMs and AI services.
Comfortable with end-to-end ownership from requirement analysis, solution design to deployment automation in Agile/Scrum environments.
Demonstrates knowledge of scalable code practices, secure coding, authentication flows, performance/load testing, and AI model evaluation and monitoring.