AI Application Developer

Questronix Corporation 2; Makati; On-site; PHP 600,000 - 1,000,000; Full time

Job summary

Questronix Corporation 2 is seeking an AI/ML backend engineer to develop and support AI-driven knowledge-base apps. You will build data pipelines and implement parsing, preprocessing, and chunking for RAG workflows.

You will help deploy services with Docker/Kubernetes, work on embeddings and vector databases, and contribute to API development using Django or FastAPI. Strong data-centric and team skills are essential.

Qualifications

• Bachelor's degree in Computer Science, Information Technology, Data Science, or related field.
• Experience with AI/ML, data engineering, or backend development in production.
• Solid understanding of AI/ML concepts including embeddings and vector databases.
• Proficient in Python and libraries such as pandas, numpy, openpyxl, requests, PyPDF.
• Hands-on data pipelines experience for structured and unstructured data.
• Experience with vector databases and similarity search.
• Familiar with Docker and Kubernetes for deployment and scaling.
• Experience with API development using Django or FastAPI.
• Familiar with CI/CD, Git, and Agile methodologies.
• Strong problem-solving, communication, and cross-functional collaboration skills.

Responsibilities

• Develop and support AI-driven apps focusing on knowledge base ingestion and data extraction.
• Build and maintain data pipelines for machine learning models.
• Implement document parsing, text preprocessing, and chunking for RAG systems.
• Design workflows to retrieve data and inject context into prompts.
• Assist in backend development using Django frameworks.
• Collaborate to test, deploy, and improve AI models and pipelines.
• Support containerized deployments with Docker and Kubernetes.
• Contribute to reducing hallucinations and improving response accuracy.

Skills

Python

Pandas

Numpy

OpenPyXL

Requests

PyPDF

Django

FastAPI

Docker

Kubernetes

Vector databases

Embeddings

RAG architecture

API development

Git

CI/CD

Agile

Prompt engineering

Education

Bachelor's degree in Computer Science or related field

Tools

Docker

Kubernetes

Django

FastAPI

Job description

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.