Applied AI Engineer（Lead）

Company Description SIGQ Inc. is a Japan-based technology company focused on incident management and resilient data infrastructure for startups and enterprises. The team designs strategic incident response frameworks that enhance system reliability and streamline cross-functional communication. SIGQ also builds scalable data lakes and data warehouses tailored to business and analytics requirements, and provides hands-on support across DevOps, SRE, and data engineering. Its mission is to bridge engineering operations and business continuity, helping organizations prepare for rapid growth and unexpected disruptions. Applicants can expect to work in an environment dedicated to building systems that scale, recover, and evolve.

Role Description The Applied AI Engineer (Lead) is a full-time hybrid role based in Tokyo, with flexibility for partial work from home. This role involves leading the design, development, and deployment of applied AI solutions that support incident management, operational resilience, and data-driven decision-making. Day-to-day responsibilities include building and optimizing machine learning models, collaborating with engineering and business teams to integrate AI into production systems, and improving tools for monitoring, alerting, and automated remediation. The Lead Engineer will mentor other team members, establish best practices for AI-driven software development, and contribute to architectural decisions across data and infrastructure projects. The position also requires staying current with AI research and tools, and translating emerging techniques into practical, reliable implementations.

Qualifications

• Strong foundation in Computer Science and Software Development, with experience building production-grade systems
• Hands-on expertise in Pattern Recognition and Neural Networks for real-world problem solving
• Practical experience with Natural Language Processing (NLP), especially for incident analysis, documentation, or automation use cases
• Proficiency in one or more modern programming languages (e.g., Python, Go, Java) and common ML frameworks (e.g., PyTorch, TensorFlow)
• Experience designing, training, and deploying machine learning models in cloud or hybrid environments
• Understanding of data engineering practices, scalable data architectures, and MLOps workflows
• Ability to collaborate effectively with cross-functional teams and communicate complex technical topics in clear terms
• Track record of technical leadership, mentoring, or ownership of significant AI or data-driven projects
• Bachelor’s degree or higher in Computer Science, Engineering, Mathematics, or a related field, or equivalent practical experience
• Business-level English; Japanese proficiency is a plus but not required