>> Architect and design end-to-end Generative AI solutions for enterprise use cases
>> Lead development using Large Language Models (LLMs), Small Language Models (SLMs), and Agentic AI / multi-agent systems
>> Define architecture for RAG (Retrieval-Augmented Generation) pipelines, AI orchestration and autonomous workflows, and scalable model deployment strategies
>> Drive solution design discussions with stakeholders and leadership teams
>> Provide technical leadership to data scientists, ML engineers, and developers
>> Establish best practices for prompt engineering, model fine-tuning, evaluation and benchmarking
>> Design and implement LLMOps / MLOps frameworks
>> Ensure governance, security, and responsible AI practices (bias, explainability, compliance)
>> Collaborate with business teams to translate requirements into scalable AI architectures
Requirements:
>> 12+ years in Data Science / AI / Machine Learning
>> Strong hands-on experience with Generative AI & LLMs (GPT, LLaMA, etc.), Small Language Models (SLMs), Agentic AI / autonomous AI systems
>> Expertise in Python, PyTorch / TensorFlow, NLP and deep learning, Prompt engineering and RAG architectures
>> Experience with model fine-tuning and embeddings, vector databases (Pinecone, FAISS, etc.), API-driven AI services
>> Strong architecture experience in Cloud platforms (AWS / Azure / Google Cloud Platform), Scalable distributed systems
>> Proven experience in enterprise-level AI solution design"
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