Take ownership of an existing AI-powered application through structured knowledge transfer, including understanding and documenting architecture, codebase, and integrations
Provide ongoing application support including bug fixing, enhancements, incident resolution, performance tuning, and stability improvements
Design, develop, and deploy end-to-end AI applications using LLMs, RAG, and agentic frameworks
Build MCP-based tool integrations and agentic workflows to connect AI solutions with enterprise systems and processes
Translate business requirements into scalable AI-powered solutions with robust backend and frontend design
Develop and integrate APIs, application logic, and user-facing features for AI-driven use cases
Implement monitoring, observability, and evaluation mechanisms for AI models, prompts, and agent behavior
Collaborate with cross-functional stakeholders to deliver pro...
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