Leads customer implementations of LLM and generative-AI systems from architecture through production, building full-stack solutions and improving model quality.
About this role
This role sits in the enterprise AI and cloud platform organization, supporting corporate customers that are applying AI, cloud, and data technologies to business and management challenges. The team works across sales, consulting, development, operations, and partner companies to deliver solutions from initial proposals through production adoption.
The engineer develops AI-enabled applications and AI agents, supports generative AI, LLM, data and analytics platforms, and designs cloud foundations using Azure, AWS, Google Cloud, or internal cloud services. Work may include customer discovery, requirements definition, architecture, construction, PoCs, operational design, cloud security, AI governance, and delivery improvement. The role also covers Databricks or Microsoft Fabric data platforms, LLM Ops, PlatformOps, DevOps, and multi-cloud standardization.
Applicants must have experience developing AI-enabled applications or AI agents, experience proposing, designing, building, or introducing a cloud service such as Azure, AWS, or Google Cloud, and experience in at least one phase of an enterprise IT project, including requirements definition, design, implementation, migration, or operations design. They must also be able to understand customer issues and explain or propose technical solutions clearly.
This is an AI-generated summary of the employer's original posting — details can be incomplete, out of date or simply wrong. Always confirm everything on the official posting before applying.
Similar jobs
Leads enterprise AI implementations from requirements to production, designing architecture, data connectivity, and RAG pipelines while guiding technical standards in a hybrid Tokyo role.
Plans and develops EMS services for homes and commercial users, integrating batteries and solar devices with web/mobile apps, cloud systems, APIs, and AI-based demand and generation forecasting.
Build data pipelines and machine-learning models for commercial real estate, tune inference, and lead AI product PoCs and MVPs with business teams. Hybrid remote work is available in Tokyo.
The role involves various responsibilities with potential for transfers and business trips across locations.
Lead multiple product teams for Fanicon, aligning business, product, and technology. Manage engineers, support technical decisions, and improve processes, quality, and team growth.