Senior Generative AI Engineer

10+ years Proficiency in Python and experience with Langchain, pyspark, PyTorch, Tensorflow, Streamlit and other relevant tools

" Prompt Engineering and AI Chatbot Acumen: Developing sophisticated AI chatbot solutions, including QA/chatbots, translation, and search/summarization functionalities.

" 5+ years of experience in GenAI Foundation Models and Vector DB: Leveraging foundational AI models and vector database technologies (multi vector) for advanced AI capabilities.

" 5+ years of experience in RAG (Retrieval-Augmented Generation) and Model Fine Tuning: Employing RAG techniques for enhanced AI responses and fine-tuning AI models for optimal performance.

" Use of Orchestration Tools: Utilizing advanced tools like Semantic Kerner, Langchain, and others for efficient AI model management.

" Expertise in either OpenAI or Google Vertex and/or other models from Hugging face for implementing advanced language models.

" Managing high availability and efficient deployment of cloud-native applications

" Experience with hosting LLMs on-premises.

" Experience with GitOps principles and tools, such as Git, Tekton, Flux, or ArgoCD, for managing infrastructure and application deployments.

" Strong problem-solving skills and the ability to work in a collaborative and fast-paced environment.

" 5+ years of experience in Automated Artificial Intelligence Tools

" 5+ years of experience in Machine Learning / AI

" 5+ years of experience in AWS, Azure, and other Cloud Platforms.

" 5+ years of experience in Docker and Kubernetes

" Bachelors or masters degree in computer science, AI, or a related field

Job Responsibilities

" This role is crucial in achieving the best RAG results on client data and contributing to the broader AI and machine learning community.

" Collaborate with cross-functional teams to understand business requirements and design AI solutions based on language models.

" Develop, train, and optimize language models using PyTorch, Tensorflow, and other relevant frameworks.

" Utilize expertise in either OpenAI or Google Vertex to implement state-of-the-art language models.

" Responsible for End-to-End RAG Solution Design and Development

" Lead the experimentation of different chunking and retrieval methods to enhance the efficiency and effectiveness of RAG systems.

" Developing, training, fine-tuning LLMs for RAG

" Conduct thorough evaluations of model and application performance.

" This entails a deep dive into model accuracy, bias identification, and the formulation of strategies for ongoing enhancement.

" Analytical skills that drive continuous improvements and set new benchmarks for excellence.

" Engage with customers from various sectors to facilitate the successful adoption of Unstructured APIs

" Bridge the gap between cutting-edge AI technology and industry-specific applications, ensuring clients achieve their strategic objectives.

" Collaborate with data scientists, software engineers, and other stakeholders to integrate AI solutions into enterprise applications.