No Japanese Required Tech Lead / Data & Backend Engineer

As demand for Generative AI solutions continues to grow rapidly, the need for robust data infrastructure and efficient data integration systems is increasing. We are looking for a Tech Lead / Data Engineer to build and manage scalable data systems that support our AI products.

Our services rely heavily on data collection, transformation, and analysis. You will help optimize these processes and enable the continued growth of our AI-powered solutions.

Role Overview

As a Tech Lead / Data & Backend Engineer, you will be responsible for designing and operating data infrastructure to support AI model training and inference.

Key Responsibilities

 Curate and manage datasets used for training AI models.

•  Perform preprocessing and feature engineering to improve model performance.

Enterprise Data Integration:

•  Design and implement systems for data integration in complex enterprise environments.
•  Enable real-time data sync using APIs and messaging queues.
•  Provide solutions for efficient cross-system data consolidation.

Database Management:

•  Design, operate, and optimize RDBMS, NoSQL, and Data Warehouses.
•  Implement backup/recovery strategies and maintain data consistency and security.

Data Quality & Security:

•  Cleanse and normalize data to ensure integrity and accuracy.
•  Define and enforce security policies and manage data access controls.

Team Structure

Our development team consists of approximately 65 members, structured into the following groups:

• Client-Facing Solution Development
• In-house AI SaaS Development
• Common Platform Development (Infra / Data / AI R&D)

Requirements

Minimum Qualifications

• Bachelor’s degree or equivalent practical experience in Computer Science, Software Engineering, AI, Machine Learning, Math, Physics, or a related field
• Experience with cloud platforms (AWS, GCP, or Azure) and container technologies (Docker, Kubernetes)
• Proven experience in technical leadership (e.g. Tech Lead, Lead Engineer, Scrum Master)
• Full-stack software development experience, including system design
• Hands-on experience with building data infrastructure or integrating data into product features
• Strong knowledge of data structures and algorithms with implementation experience
• Proficiency in Python and SQL for data processing
• Experience automating data workflows using scripting languages
• Database design, operation, and performance tuning experience
• Experience with data cleansing, normalization, and quality improvement
• Knowledge and practical experience in data security and governance
• Foundational knowledge and practical usage of LLMs / GenAI / RAG
• English: Business level or higher

Preferred Qualifications

• 3+ years of hands-on data engineering experience
• Experience designing and implementing data pipelines
• Experience working with RDBMS, NoSQL, and Data Warehouses
• Experience curating and managing datasets for AI/ML training
• Background in AI/ML, NLP, chatbot development, or agent frameworks
• Familiarity with big data technologies (e.g., Hadoop, Spark)
• Experience working in multinational or multicultural environments

Tech Stack / Tools

• Languages: Python (Backend), TypeScript / React / Next.js (Frontend) / NX
• Infrastructure: GCP (Kubernetes), Docker
• Tools: Slack, Confluence, Linear, Google Workspace, GitHub, Notion
• Hardware: Mac (Apple Silicon), dual monitors