AI Application Developer

<h2>Job Description:</h2><ul><li>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).</li></ul><ul><li>Build and maintain data pipelines for machine learning models, ensuring data quality, consistency, and efficient processing.</li></ul><ul><li>Implement document parsing, text preprocessing, and chunking strategies to prepare data for retrieval-augmented generation (RAG) systems.</li></ul><ul><li>Design and support workflows for retrieving relevant data and injecting context into prompts for AI applications.</li></ul><ul><li>Assist in developing and integrating backend services using Python frameworks such as Django.</li></ul><ul><li>Collaborate with cross-functional teams to test, deploy, and improve AI models and pipelines.</li></ul><ul><li>Support containerized deployments and environments using Docker and Kubernetes.</li></ul><ul><li>Contribute to continuous improvement of AI systems, including reducing hallucinations and improving response accuracy.</li></ul><h2>Requirements</h2><h2>Qualification:</h2><ul><li>Bachelor’s degree in Computer Science, Information Technology, Data Science, or any related field.</li></ul><ul><li><strong>years of experience in AI/ML, data engineering, or backend development with exposure to production-level AI systems.</strong></li></ul><ul>
<li>Strong understanding of AI/ML concepts, including embeddings, vector databases, and RAG architecture design.</li>
<li><strong>Proficient in Python and relevant libraries such as pandas, numpy, openpyxl, requests, and PyPDF.</strong></li>
<li>Hands-on experience in building and optimizing data pipelines for structured and unstructured data.</li>
<li>Strong experience in data preprocessing, document parsing, chunking strategies, and normalization techniques.</li>
<li><strong>Experience working with vector databases and similarity search mechanisms.</strong></li>
<li><strong>Familiar with Docker and Kubernetes for containerized deployment and scaling.</strong></li>
<li><strong>Experience with Dify platform or similar AI workflow/orchestration tools is an advantage.</strong></li>
<li>Strong understanding of prompt engineering, context injection, and techniques to minimize hallucinations in AI systems.</li>
<li><strong>Experience with API development and system integration using frameworks such as Django or FastAPI.</strong></li>
<li><strong>Familiar with CI/CD pipelines, version control (Git), and Agile methodologies.</strong></li>
<li>Strong problem-solving, analytical, and communication skills, with the ability to work across cross-functional teams.</li>
</ul>