AI Solution Engineer

Department Business Intelligence and Data Analytics

LevelExperienced (Individual Contributor)

LocationJakarta

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:

• Execute the building, testing, and maintenance of AI-enabled tools and services for internal systems within the designated project phases.
• Implement and integrate language models and advanced AI components into existing workflows and platforms to meet project delivery milestones.
• Coordinate with cross-functional stakeholders, including engineering, operations, and product teams, to drive AI adoption and understand critical project use cases.
• Analyze data, support model testing, evaluate performance, and assist in seamless model integration into internal systems.
• Manage the development of internal APIs, automation scripts, dashboards, and data pipelines throughout the project lifecycle.
• Monitor the performance of deployed models and services, proactively debugging and iterating to ensure robust project deliverables.

Requirements:

• Hold a Bachelor’s degree in Computer Science, Engineering, or a related technical field.
• Possess 2+ years of professional software development experience (or strong computer science fundamentals for recent graduates).
• Demonstrate strong proficiency in Python for AI or backend system development (Golang is a major advantage).
• Show solid core CS fundamentals, including algorithms, data structures, system design, and basic machine learning principles.
• Have proven experience in backend development and cloud-ready services (APIs, databases, and message queues).
• Familiar with modern AI frameworks and tools (e.g., LangChain, LangGraph, Transformers, and OpenAI APIs).
• Understand key AI methodologies, including prompt engineering, embeddings, Retrieval-Augmented Generation (RAG), and multi-agent systems.
• Prior exposure to deploying production-ready AI systems via APIs, containers (Docker), or cloud infrastructure.
• Exhibit a strong analytical and problem-solving mindset with a proactive willingness to experiment, learn, and iterate.
• Maintain a genuine passion for engineering practical, reliable, and scalable AI solutions to address real internal business problems.