DynPro Inc.
Generative AI Engineer with React
DynPro Inc., San Francisco, California, United States, 94101
Only LOCAL to San Francisco Bay Area, CAResponsibilities
Develop GenAI applications using NLP techniques and Open AI , and validate outputs using APIs.Enable various GenAI business use cases utilizing client infrastructure with a focus on security and governance.
Ability to develop complex
applications in LLM , including developing chatbots
Integrate generative models or applications into existing systems and workflows seamlessly.
Implement effective prompt techniques to reduce token usage and improve output accuracy.
Integrate disparate structured and unstructured datasets and documents into a vector database for an effective
RAG system
Document processes, models, and code to ensure maintainability and reproducibility.
Required skill set
8 + years of experience in developing applications using data, AI/ML using
Python,
Langchain, Streamlit
etc2+ years of Experience with development using LLMs.4+ Years of experience with frontend development experience with modern web technologies (React, Angular).Solid understanding of RAG, embedding, and training LLMs.Technical know-how of effective prompt engineering.Hands-on expertise on various Azure services such as
Azure Search, App Services, APIManagement, Cosmos DBFamiliarity with managing Azure cloud infrastructure.Familiarity with Web technologies like ReactFamiliarity with software development best practices, including version control (Git), testing, and continuous integration/continuous deployment (CI/CD).
Develop GenAI applications using NLP techniques and Open AI , and validate outputs using APIs.Enable various GenAI business use cases utilizing client infrastructure with a focus on security and governance.
Ability to develop complex
applications in LLM , including developing chatbots
Integrate generative models or applications into existing systems and workflows seamlessly.
Implement effective prompt techniques to reduce token usage and improve output accuracy.
Integrate disparate structured and unstructured datasets and documents into a vector database for an effective
RAG system
Document processes, models, and code to ensure maintainability and reproducibility.
Required skill set
8 + years of experience in developing applications using data, AI/ML using
Python,
Langchain, Streamlit
etc2+ years of Experience with development using LLMs.4+ Years of experience with frontend development experience with modern web technologies (React, Angular).Solid understanding of RAG, embedding, and training LLMs.Technical know-how of effective prompt engineering.Hands-on expertise on various Azure services such as
Azure Search, App Services, APIManagement, Cosmos DBFamiliarity with managing Azure cloud infrastructure.Familiarity with Web technologies like ReactFamiliarity with software development best practices, including version control (Git), testing, and continuous integration/continuous deployment (CI/CD).