This is a remote position.
Role PurposeTo lead the end-to-end architecture, design, and deployment of advanced, scalable Generative AI solutions. This highly specialized role is at the forefront of AI innovation, responsible for selecting and orchestrating the complex components required to build high-performance Generative AI systems.
• Generative AI Solution Design: Lead the architecture of complex GenAI systems, including Large Language Model (LLM) selection, fine-tuning strategies, and the design of Retrieval-Augmented Generation (RAG) pipelines.
• Technology Stack Expertise: Build scalable solutions using cloud AI services (e.g., Azure AI, AWS Bedrock) and open-source frameworks like LangChain and LlamaIndex. Write efficient Python code for data processing and APIs.
• Model and System Optimization: Enhance model performance, scalability, and cost-efficiency through prompt engineering, model quantization, and efficient data pipeline design.
• Vector Database Management: Design and implement solutions using vector databases (e.g., Pinecone, Weaviate, Chroma) for efficient similarity search in RAG systems.
• MLOps for GenAI: Implement CI/CD pipelines and containerization (Docker, Kubernetes) for the continuous integration and deployment of Generative AI models.
• Technical Leadership & Innovation: Provide expert guidance to development teams on GenAI best practices. Stay updated on the latest trends in LLMs and diffusion models, and drive proof-of-concept projects and pilot implementations.
• Stakeholder Collaboration: Work with cross-functional teams to align GenAI solutions with business goals and effectively communicate highly technical concepts to non-technical stakeholders.
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