IT Application Developer

General Responsibilities:

1.  Technically responsible for the development of the AI/ML model (including training, evaluation, and deployment) as well as active communication with AI vendors or third-party technology providers. 2  Perform cross-division internal collaborations (including with data engineers, developers, and business teams) to ensure relevant and value-added AI solutions. 3.  Designing, building, and implementing AI/ML-based solutions to support business needs (such as predictions, automation, recommendations, etc.). 4.  Create technical documentation (model architecture, hyperparameter, data pipeline) and functional on AI solutions developed. 5.  Using programming languages and AI/ML frameworks that comply with enterprise standards, such as Python, TensorFlow, PyTorch, Scikit-Learn, or others. 6  Testing the AI model, including the test unit, pipeline integration, and validation of the results of the model alongside business users. 7.  Doing tuning or redeveloping models based on user feedback or data changes (model retraining and continuous learning). 8  Ensuring AI solutions run optimally, stably, and securely, implement secure coding practices, and store code and models on the version control repository. 9.  Perform routine monitoring of the performance of the AI model (e.g. using MLflow, Prometheus, or custom dashboard) to detect drift or error models. 10.  Handle bugs or errors in data pipelines or AI models, as well as debugging and troubleshooting. 11.  Provides technical support for internal users who utilize the output of the AI system (dashboard, API, or system integration). 12.  Update the pipeline and model to ensure performance and compatibility with the latest technology and data. 13.  Communicate with AI technology provider vendors for updates, technical consulting, or system integration. 14.  Ensure AI solutions comply with information security standards, including sensitive data encryption, data anonymization, and authentication and authorization-based access. 15.  Ensure AI solutions comply with applicable regulations, such as GDPR, Personal Data Protection Act, and related industry regulations. 16.  Coordinate with the IT security team to ensure the AI system does not become a vulnerability vector and maintains data integrity. 17.  Transfer knowledge to the internal team through documentation, workshops, or internal training sessions to ensure the sustainability of AI projects. 18.  Providing training to end users in understanding the use and interpretation of the results of the AI system built. 19.  Conduct research and exploration of the latest technologies in the field of AI/ML (including LLM, edge AI, and AutoML) that are relevant to the company. 20.  Providing recommendations on new technologies or approaches that can improve operational efficiency through AI

Requirements:

• Candidate should possess minimum Bachelor Degree (S1), majoring IT, Computer Science, Software Engineering, or related IT fields

• Minimum of 3 years of working experience in the same field.

Programming Experience

• Minimum 2 years of experience using programming languages, primarily Python for AI/ML development.

• Familiar with backend frameworks such as FastAPI, Flask, or Django.

Frontend Development

• Familiar with frontend technologies when AI integration is needed in products, including React, Next.js, and dashboard libraries like Streamlit or Dash.

Source Code Management

• Experienced with Git, including best practices for branching strategies and pull requests.

Testing & Model Validation

• At least 1 year of experience in unit testing and AI model validation using techniques like cross-validation and A/B testing.

Secure Coding

• Knowledge of secure coding practices, especially when handling sensitive data in AI/ML systems.

Team Collaboration

• Able to work independently or collaboratively with cross-functional teams such as data engineers, developers, and business analysts.

Containerization

• Experienced in using Docker to package AI models and pipelines into portable and reproducible containers.

MLOps

• Basic understanding of MLOps, including:

  • Deployment using CI/CD pipelines

  • Cloud model management with tools like AWS SageMaker or GCP Vertex AI

  • Familiarity with MLflow, Kubeflow, or similar tools

AI Frameworks & Libraries

• Proficient in using libraries such as TensorFlow, PyTorch, Scikit-learn, and supporting tools like Pandas, NumPy, and Matplotlib.

Data Analysis & Statistics

• Strong skills in data analysis and statistical understanding to effectively structure models and evaluate AI solution performance.

• Special Qualification: Minimum Risk Management Certification in accordance with the provisions of regulations and the level of position of the organizational structure under the Board of Directors

• Minimum implementation experience of 3 projects with the SDLC method.

• Understanding Banking Regulations 

Information :

• Company : Bank JTrust Indonesia
• Position : IT Application Developer
• Location : Jakarta Pusat
• Country : ID