onsite
Generative AI Engineer - LLM & RAG
Generative AI Engineer
The Generative AI Engineer will design, develop, and deploy scalable AI-driven applications, focusing on Generative AI and LLM-based solutions. This role involves building production-ready machine learning systems, implementing RAG solutions, and collaborating with cross-functional teams in an Agile environment.
About the role
About Role
We are seeking a highly skilled Data Scientist with strong expertise in AI/ML, Generative AI, and LLM-based solutions. The ideal candidate will be responsible for designing, developing, and deploying scalable AI-driven applications using modern tools and frameworks. This role requires hands-on experience in building production-ready machine learning systems and working in a collaborative Agile environment.
Key Responsibilities
- Design, develop, and deploy AI/ML solutions using Python.
- Build and integrate Generative AI applications using OpenAI APIs and LLM-based workflows.
- Implement Retrieval-Augmented Generation (RAG) solutions for intelligent information retrieval.
- Develop interactive AI applications and prototypes using Streamlit.
- Utilize Snowflake for data processing, analytics, and feature engineering.
- Design and maintain scalable, production-grade ML pipelines.
- Collaborate with product, data engineering, and business teams to deliver AI solutions.
- Optimize model performance, cost efficiency, and system reliability.
- Support deployment, monitoring, and continuous improvement of AI/ML applications.
- Contribute to AI architecture design and best practices within the organization.
Required Skills & Qualifications
- 5+ years of experience in Python development.
- Strong hands-on experience with OpenAI APIs and prompt engineering.
- Working knowledge of Snowflake (basic to intermediate level).
- Experience in building applications using Streamlit.
- Solid understanding of Machine Learning concepts and data pipelines.
- Strong knowledge of RAG (Retrieval-Augmented Generation) and Generative AI concepts.
- Experience with CI/CD pipelines and application deployment.
- Exposure to working in Agile development environments.
- Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering.