AI Data Pipelines & Applications Engineer

Questronix Corporation; Philippines; On-site; PHP 400,000 - 640,000; Full time

Job summary

Questronix Corporation in the Philippines seeks a developer to build and support AI-driven applications for knowledge base ingestion, including extracting, processing, and storing data from Excel, PDFs, images, and databases.

You'll design data pipelines for ML models, implement document parsing and retrieval-augmented generation prep, and collaborate to test, deploy, and improve AI systems. Experience with Python (Django), Docker, and Kubernetes is a plus.

Responsibilities

• 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.

Job description

Questronix Corporation in the Philippines seeks a developer to build and support AI-driven applications for knowledge base ingestion, including extracting, processing, and storing data from Excel, PDFs, images, and databases.

You'll design data pipelines for ML models, implement document parsing and retrieval-augmented generation prep, and collaborate to test, deploy, and improve AI systems. Experience with Python (Django), Docker, and Kubernetes is a plus.