Posted:1 month ago|
Platform:
Work from Office
Full Time
Role & responsibilities Lead the architecture and deployment of LLM and GenAI-based applications. Fine-tune and optimize state-of-the-art LLMs including GPT, LLaMA, Claude, Mistral, etc. Design and implement advanced prompt engineering and Retrieval-Augmented Generation (RAG) systems. Collaborate with data scientists, backend engineers, and product teams to deliver robust AIdriven solutions. Ensure security, performance, and cost optimization in model training and deployment. Translate complex business requirements into scalable GenAI solutions. Maintain best practices in code quality, version control, and documentation. Proven expertise in LLM fine-tuning, deployment, and inference workflows. Strong experience in Prompt Engineering and RAG (Retrieval-Augmented Generation) systems. Proficient in Python with hands-on experience in building AI pipelines. Demonstrated ability to lead system design and architecture for GenAI applications Preferred candidate profile Familiarity with GenAI toolkits such as LangChain, LlamaIndex, Haystack, or custom-built frameworks. Exposure to Microsoft Azure (preferred over AWS or GCP) for cloud deployments. Experience with scalable, secure AI infrastructure and CI/CD pipelines for ML models
Cubastion Consulting
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