We are seeking a Data Engineer with strong expertise in SQL, Python, and Retrieval-Augmented Generation (RAG) application development. The ideal candidate should have hands-on experience building production-ready AI solutions using Large Language Models (LLMs) and be capable of developing, enhancing, and scaling enterprise AI applications.
Key Responsibilities
- Develop and enhance RAG-based AI applications using Python and SQL.
- Perform data extraction, transformation, and analysis on structured and unstructured data.
- Build conversational AI solutions that enable natural language querying of business data.
- Enhance AI-powered document analysis tools by improving data ingestion, retrieval, and output capabilities.
- Work with document processing, embeddings, vector databases, and LLM integrations.
- Collaborate with cross-functional teams to deliver scalable AI solutions.
Experience on
1.Conversational Data Quality: A natural language interface over clinical milestone data (Excel inputs + rules) where a study manager can ask open-ended questions like "show me rule violations for sites in Spain." The point is moving beyond rigid tabular tools to a context-aware, question-driven experience.
2. ICF Analysis Tool: Already in production. Ingests "Informed Consent Form: documents from a folder, runs them through an AI engine that flags suspicious data-sharing language, surfaces offending paragraphs, allows user overrides, and exports to Excel. The hire needs to own, improve, and expand this kind of tooling.
Required Skills
- 8-10 years of experience
- Strong proficiency in Python and SQL (data extraction, transformation, and analysis).
- Hands-on experience building RAG-based AI applications(mandatory).
- Experience with LLMs, vector databases, document processing, embeddings, and AI application development.
- Strong analytical and problem-solving skills.
Good to Have
- Tableau (basic dashboard/report development is sufficient).
- Experience in the Life Sciences
Pay: From ₹1,200,000.00 per year
Work Location: Remote
