Senior AI & Data Engineer
Summary
Build and maintain an enterprise-scale data platform that powers AI agents, knowledge bases, and RAG systems using Python, GCP, and vector databases.
Location: Jakarta (Hybrid/On-site as required)
Employment Type: 1-Year Contract (Managed Service)
About the Role
We are looking for a Senior AI Platform & Data Engineer to help build and enhance an enterprise-scale Universal Data Platform (UDP). You will be responsible for integrating data from multiple business systems, developing reliable data pipelines, and enabling AI-powered applications through high-quality, well-governed data.
This role is ideal for someone who enjoys working at the intersection of Data Engineering, AI Platforms, and Generative AI, helping transform enterprise data into trusted assets for AI agents, knowledge bases, and intelligent business applications.
Key Responsibilities
Design, develop, and maintain scalable data pipelines to integrate data from multiple enterprise systems.
Build and optimize enterprise data platforms that support analytics and AI applications.
Develop and maintain Knowledge Bases, AI Copilots, semantic search, and Retrieval-Augmented Generation (RAG) solutions.
Implement data quality validation, monitoring, and anomaly detection to ensure data reliability.
Build and maintain metadata, data catalogs, and documentation to improve data discoverability and governance.
Prepare structured and unstructured data for AI applications, including indexing, chunking, and semantic retrieval.
Develop and manage vector search solutions using modern vector databases.
Deploy and maintain AI and data applications using cloud-native technologies.
Build dashboards or internal portals to visualize data quality, platform health, and AI capabilities.
Collaborate closely with business and technical stakeholders to improve enterprise data accessibility and adoption.
Requirements
Minimum 4 years of experience as a Data Engineer, AI Engineer, Analytics Engineer, or related role.
Strong proficiency in Python and SQL.
Experience building ETL/ELT pipelines and working with large-scale data platforms.
Hands-on experience with Google Cloud Platform (GCP), particularly:
BigQuery
GKE
Experience with containerization using Docker and Kubernetes.
Experience developing Generative AI applications, including RAG, Knowledge Bases, AI Chatbots, or AI Agents.
Familiarity with AI frameworks such as LangChain, LangGraph, LlamaIndex, or Dify.
Experience with vector databases such as Weaviate, Qdrant, Elasticsearch, or similar technologies.
Knowledge of data quality and observability tools such as Great Expectations, Soda, dbt Tests, or equivalent.
Experience creating dashboards using Streamlit, Metabase, Power BI, or similar visualization tools.
Preferred Qualifications
Understanding of metadata management and data catalog solutions.
Experience supporting AI/LLM applications in production environments.
Strong problem-solving skills with the ability to work independently and collaboratively.
What We're Looking For
Passion for building scalable data platforms and AI solutions.
Strong ownership of data quality and platform reliability.
Ability to design reusable and maintainable data pipelines.
Interest in emerging AI technologies and enterprise GenAI applications.
Excellent communication and stakeholder management skills.