Generative AI Architect

3 weeks ago

Madhapur, India Zyoin Group Full time

Description : Responsibilities : - GenAI Solution Delivery : Design, build, and release enterprise-grade GenAI systems, including RAG pipelines, Agentic AI systems, multimodal LLMs, and foundation models.- Agentic AI : Minimum 6-12 months of experience in developing, deploying, and managing Agentic AI systems, with a clear understanding of tool usage, structured outputs, speculative decoding, AST-Code RAG, streaming, and sync/async processing.- Fine-Tuning and PEFT : Hands-on expertise in PEFT methods (LoRA / QLoRA) for model fine-tuning and optimization.- Embedding Models : Strong knowledge of embedding models, chunking strategies, and their limitations when used in RAG pipelines.- Hands-on Coding : Write, test, and maintain clean, efficient, and scalable code in Python for building NLP and AI systems.- Cloud and Deployment : Deep familiarity with Azure and proven experience in deploying LLMs for large-scale inference using LLM Ops techniques and orchestration frameworks.- Tech Stack Proficiency : Strong expertise in PyTorch, TensorFlow, Kubernetes, Docker, Llama Index, Lang Chain, and Lang Graph.- Innovation and Research : Stay updated on the latest advancements in AI agents, LLM architectures, and orchestration tools, experimenting with emerging techniques to enhance system performance.- Communication : Strong interpersonal and communication skills, with the ability to design solutions and explain complex AI concepts to both technical and business stakeholders.Requirements : - 6-12 years of overall experience with a strong balance of business and technical acumen.- 3+ years of GenAI development and deployment experience.- Min 6-12 months of Agentic AI development experience.- Strong Python development skills.- Proven experience in RAG pipelines, embeddings, and chunking strategies.- Expertise in LoRA / QLoRA fine-tuning.- Hands-on coding for NLP and LLMs.- Proficiency in PyTorch, TensorFlow, LangChain, LangGraph, and LlamaIndex.- Deep familiarity with Azure Cloud, LLMOps, orchestration, and large-scale inference.- Knowledge of speculative decoding, AST-Code RAG, structured outputs, streaming, and async processing. (ref:hirist.tech)

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