Job Description:

• Develop and support AI-driven applications focused on knowledge base ingestion, including extracting, processing, and storing structured and unstructured data (e.g., Excel files, PDFs, images, and database records).

• Build and maintain data pipelines for machine learning models, ensuring data quality, consistency, and efficient processing.

• Implement document parsing, text preprocessing, and chunking strategies to prepare data for retrieval-augmented generation (RAG) systems.

• Design and support workflows for retrieving relevant data and injecting context into prompts for AI applications.

• Assist in developing and integrating backend services using Python frameworks such as Django.

• Collaborate with cross-functional teams to test, deploy, and improve AI models and pipelines.

• Support containerized deployments and environments using Docker and Kubernetes.

• Contribute to continuous improvement of AI systems, including reducing hallucinations and improving response accuracy.

Requirements

Qualification:

• Bachelor’s degree in Computer Science, Information Technology, Data Science, or any related field.

• years of experience in AI/ML, data engineering, or backend development with exposure to production-level AI systems.

• Strong understanding of AI/ML concepts, including embeddings, vector databases, and RAG architecture design.
• Proficient in Python and relevant libraries such as pandas, numpy, openpyxl, requests, and PyPDF.
• Hands-on experience in building and optimizing data pipelines for structured and unstructured data.
• Strong experience in data preprocessing, document parsing, chunking strategies, and normalization techniques.
• Experience working with vector databases and similarity search mechanisms.
• Familiar with Docker and Kubernetes for containerized deployment and scaling.
• Experience with Dify platform or similar AI workflow/orchestration tools is an advantage.
• Strong understanding of prompt engineering, context injection, and techniques to minimize hallucinations in AI systems.
• Experience with API development and system integration using frameworks such as Django or FastAPI.
• Familiar with CI/CD pipelines, version control (Git), and Agile methodologies.
• Strong problem-solving, analytical, and communication skills, with the ability to work across cross-functional teams.