Data Scientist - Generative AI

<p><p><b>Role Overview :</b><br/><br/>We are looking for a highly skilled GenAI Data Scientist proficient in cutting-edge Generative AI frameworks and tools such as Agentic AI, LangGraph, LlamaIndex, and OpenAI.<br/><br/>The ideal candidate will translate complex business requirements into scalable AI solutions, creating production-ready systems that leverage the latest advances in generative models and AI agents.<br/><br/>Strong Python and Streamlit development expertise is essential to build interactive prototypes and deploy AI applications.<br/><br/><b>Key Responsibilities :</b><br/><br/>- Design, develop, and deploy innovative generative AI models and AI agents using leading frameworks and platforms.<br/><br/>- Translate complex business challenges into algorithmic solutions by leveraging GenAI tools and libraries like LangGraph, LlamaIndex, and OpenAI APIs.<br/><br/>- Develop interactive AI applications and dashboards primarily using Python and Streamlit to showcase AI capabilities and enable user engagement.<br/><br/>- Collaborate with cross-functional teams to integrate AI solutions into business workflows, emphasizing scalability, robustness, and maintainability.<br/><br/>- Conduct model training, fine-tuning, and evaluation while ensuring ethical AI use and mitigating biases.<br/><br/>- Support deployment and production environments with continuous monitoring, troubleshooting, and optimization of AI systems.<br/><br/>- Stay updated with advancements in GenAI research and apply best practices for prompt engineering, large language models, and retrieval-augmented generation.<br/><br/><b>Required Skills and Qualifications :</b><br/><br/>- Proven experience in Generative AI and Agentic AI frameworks, with hands-on usage of LangGraph, LlamaIndex, and OpenAI.<br/><br/>- Strong proficiency in Python programming and building web-based interactive applications with Streamlit or similar frameworks.<br/><br/>- Deep understanding of AI/ML lifecycle including data preprocessing, model development, hyperparameter tuning, and deployment workflows.<br/><br/>- Ability to translate business needs into AI-driven solutions, collaborating effectively with stakeholders.<br/><br/>- Demonstrated skills in responsible AI, bias detection, and explainability techniques.<br/><br/>- Experience deploying AI solutions to production, ensuring performance and reliability under real-world conditions.<br/><br/><b>Recommended Experience :</b><br/><br/>- 3 to 7 years in data science or AI roles with significant exposure to generative AI technologies and practical deployment experience<br/></p><br/></p> (ref:hirist.tech)