Department Business Intelligence and Data Analytics
LevelExperienced (Individual Contributor)
LocationIndonesia - Jakarta
The Business Intelligence and Data Analytics team plays a critical role in conducting close-loop data-driven business iterations. As business intelligence specialists and data analysts, our scope of work is not limited to just performance monitoring and reporting, but also in proactively finding actionable insights to help drive high-impact business changes. Our end-to-end data solution reduces the gap between the business teams and technical teams, and achieves real ‘intelligence’ in the iteration cycle. Browse our Business Intelligence and Data Analytics team openings to see how you can make an impact with us.
Job Description:
- Collaborate with other AI engineers to build, test, and maintain AI-enabled tools and services for internal use
- Integrate language models and other AI components into existing workflows and platforms
- Collaborate with cross-functional stakeholders (engineering, operations, product) to understand use cases and support AI adoption
- Assist in data preparation, model testing, evaluation, and integration into internal systems
- Contribute to the development of internal APIs, automation scripts, dashboards, and pipelines
- Participate in design reviews, code reviews, and technical discussions to continuously improve engineering standards and code quality
- Monitor performance of deployed models and services, and support basic debugging and iteration
Requirements:
- Bachelor’s degree in Computer Science, Engineering, or a related field
- 2+ years of software development experience, or strong fundamentals for new grads
- Proficiency in Python for building AI or backend systems; Golang is a plus
- Strong CS fundamentals — algorithms, data structures, systems design, and basic ML principles
- Experience with backend development and cloud-ready services (e.g., APIs, databases, queues)
- Familiarity with modern AI tools and frameworks (e.g., LangChain, LangGraph, Transformers, OpenAI APIs)
- Understanding of key AI concepts such as prompt engineering, embeddings, RAG, or multi-agent systems
- Exposure to deploying AI systems in production (e.g., via APIs, containers, or cloud platforms)
- Strong analytical and problem-solving mindset with a willingness to experiment and iterate
- Passion for building practical, reliable AI systems that solve real internal problems at scale
Laporkan lowongan
