5.0 - 10.0 years

0 Lacs

hyderabad, telangana

On-site

As a GenAI Technical Solutions Architect, your role involves developing and implementing architecture strategies for Gen AI to enhance AI ML model deployment and monitoring efficiency. You will focus on developing cutting-edge architectural strategies for Gen AI components and platforms, leading the implementation of LLM operations, and working closely with data scientists and AI professionals to drive digital transformation. Your responsibilities include: - Developing cutting-edge architectural strategies for Gen AI components and platforms, leveraging advanced techniques such as chunking, Retrieval-Augmented Generation (RAG), AI agents, and embeddings. - Leading working sessions for Arch Alignment, pattern library development, GEN AI Tools Data Architect alignment, and identifying components for reuse to save efforts, time, and money. - Leading the implementation of LLM operations to optimize model performance, scalability, and efficiency, and designing autonomous AI systems capable of complex decision-making and task execution. - Working closely with data scientists and AI professionals to identify and pilot innovative use cases aligned with business objectives and ROI. - Defining AI architecture, selecting suitable technologies, integrating RAG systems, embedding models, and LLM frameworks, and deciding on optimal deployment models. - Auditing AI tools and practices for continuous improvement, collaborating with security and risk leaders to ensure ethical AI implementation, and staying updated on AI regulations. You should have: - Proven track record in shipping products and developing Gen AI product architecture, with 10+ years of experience in AI and 5+ years in building NLP/AI software. - Demonstrated experience in delivering Gen AI products, deep familiarity with cloud technologies, proficiency in PyTorch, TensorFlow, Kubernetes, Docker, and experience deploying models using advanced LLM ops techniques. - Excellent communication and interpersonal skills, hands-on experience with chunking strategies, RAG implementation, and optimizing embedding models. Qualifications: - Bachelor's or master's degree in computer science, Data Science, or a related technical field. - Ability to translate complex technical concepts into actionable business strategies, strong communication skills, and a proven track record in managing and delivering AI/ML projects in large-scale enterprise environments.,

Posted 15 hours ago

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