AI Engineer

You are as unique as your background, experience and point of view. Here, you’ll be encouraged, empowered and challenged to be your best self. You'll work with dynamic colleagues - experts in their fields - who are eager to share their knowledge with you. Your leaders will inspire and help you reach your potential and soar to new heights. Every day, you'll have new and exciting opportunities to make life brighter for our Clients - who are at the heart of everything we do. Discover how you can make a difference in the lives of individuals, families and communities around the world.

Job Description:

Job description / Description du poste

• build and deploy AI and machine learning models, and automation workflows that address validated business use cases across SLI functions including Operations, Distribution, and Customer Service
• Integrate AI solutions with SLI's existing systems and platforms ; ensure AI outputs are reliable, explainable, and production-stable .
• Work closely with the Data team to ensure AI models have access to clean, well-structured, and governance-compliant data; contribute to feature engineering and training data curation in coordination with Data team .
• Monitor deployed AI models for performance drift, data quality degradation, and accuracy; implement retraining pipelines and maintain model versioning to ensure consistent output quality in production.
• Document AI architecture , model cards, and technical decisions; share learnings with the broader IT & Digital team to build internal AI capability and support responsible AI governance

Preferred skills / Compétences particulières

• Machine Learning and LLM integration experience: prompt engineering, RAG (Retrieval Augmented Generation), API integration with LLM providers
• Python proficiency for AI/ML development and data processing
• Cloud AI services: AWS SageMaker, AWS Bedrock, or equivalent (AWS preferred given SLI cloud footprint)
• Software development practices: develop, build, test, monitoring
• Data engineering fundamentals: ability to work with SQL, NoSQL and vector database
• Understanding of responsible AI principles and explainability requirements

Qualifications / Compétences

• Bachelor’s degree in computer science , Data Science, Artificial Intelligence, or a related field. Master's degree is an advantage.
• Minimum 2-4 years of hands-on AI/ML engineering experience with models deployed to production.
• Experience in financial services or insurance AI use cases is an advantage.
• Proficiency in English; Bahasa Indonesia .

Responsibilities / Responsabilités

• Collaborating with development team to deliver AI solutions
• Documenting and manage versioning of the model
• collaborating with devsecops team to create model deployment pipeline
• Keep update with AI recent trends

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