Lead architecture, design, and deployment of scalable GenAI/ML systems.
Develop end-to-end GenAI features incl. backend APIs, model integration, monitoring.
Integrate and optimise LLMs for planning; prompt engineering and RAG.
Build conversational interfaces and agentic workflows for natural language planning.
Implement evaluation frameworks for GenAI quality.
Design APIs exposing AI capabilities to the platform and integrations.

🎯 Requirements

Extensive hands-on experience in AI/ML or related engineering domains.
End-to-end model lifecycle development, including training and production deployment.
Deep knowledge of LLM APIs, prompt engineering, and conversational AI.
Experience fine-tuning LLMs for enterprise applications.
Strong expertise in MLOps and LLMOps for scalable deployments.
Proficiency in Python and modern software development practices (CI/CD, testing).

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