Application Programming Interface (API), Artificial Intelligence (AI), Best Practices, Data Management, Data Modeling, Database Design, Management Strategy, Microservices, Scalable System Development, Shallow Parsing, Use Cases
Job Summary:- Develop pipelines to parse documents, chunk, vectorise, and store vector data.
- Design schemas for vector stores to optimise retrieval efficiency.
- Create prompt templates using advanced prompt engineering techniques.
- Implement few-shot prompting strategies for improved LLM interactions.
- Develop semantic agents and interfaces for seamless agent collaboration.
- Build microservices and expose them as APIs for scalable solutions.
- Work closely with architects and full-stack developers to deliver AI solutions.
- Apply best practices for data management and model deployment.
- Ensure scalability and performance of generative AI applications.
Must-Have Skills- Designed and developed scalable generative AI platforms for enterprise use cases.
- Built end-to-end pipelines for document parsing, chunking, vectorisation, and storage in vector databases like FAISS, Pinecone, and Chroma.
- Created and optimised vector store schemas for efficient semantic retrieval.
- Developed prompt templates using few-shot and zero-shot prompting techniques.
- Engineered semantic agents and built interfaces for agent collaboration in LLM workflows.
- Built and deployed microservices exposing LLM capabilities through scalable APIs.
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Macpower Digital Assets Edge Private Limited