Roles & Responsibilities
- Develop enterprise-level GenAI applications using LLM frameworks such as Langchain , Autogen , and Hugging Face.
- Design and develop intelligent pipelines using PySpark , TensorFlow, and PyTorch within Databricks and AWS environments.
- Implement embedding models and manage VectorStores for retrieval-augmented generation (RAG) solutions.
- Integrate and leverage MDM platforms like Informatica and Reltio to supply high-quality structured data to ML systems.
- Utilize SQL and Python for data engineering, data wrangling, and pipeline automation.
- Build scalable APIs and services to serve GenAI models in production.
- Lead cross-functional collaboration with data scientists, engineers, and product teams to scope, design, and deploy AI-powered systems.
- Ensure model governance, version control, and auditability aligned with regulatory and compliance expectations.
Basic Qualifications and Experience
- Master's degree with 4 - 6 years of experience in Business, Engineering, IT or related field OR
- Bachelor's degree with 6 - 9 years of experience in Business, Engineering, IT or related field OR
- Diploma with 10 - 12 years of experience in Business, Engineering, IT or related field
