Applied AI Engineer

Job Description ■Mid-to-Long-Term Mission ・Leading a cluster of AI products as a single domain, rather than focusing on single features. ・Creating a repeatable pattern for the process from model development to application implementation and operation, in collaboration with domain-specialized data scientists, and rolling it out to other services. ・Experimenting with and standardizing the use of AI across the entire development organization (e.g., AI coding agents, documentation generation). ■Responsibilities ・Designing the AI solution approach by organizing the problem statement and success metrics collaboratively with the Product Manager and Business (Biz) members. ・Developing features, from prototypes to production-ready functionalities, using LLMs and machine learning models. ・Implementing on the existing microservice / batch infrastructure (e.g., API creation, batch processing, workflow construction). ・Designing the operation for the production environment and running the monitoring, alerting, and improvement cycle. ・Providing feedback from the application side for the maintenance and improvement of the existing MLOps infrastructure (e.g., GKE / workflow platform). ■ AI Environment ・NotionAI ・OpenAI ・Claude ・Gemini ・NotebookLM ・CURSOR ・Devin ■ Technology Stack ・Frontend: React, TypeScript ・Backend: Go/gRPC, NestJS/GraphQL ・Database: PostgreSQL ・Data Engineering/Analytics: Python ・Mobile: Flutter ・Infrastructure: GCP, GKE, Argo Workflows, BigQuery, Pub/Sub, Dataflow, etc ・IaC: Terraform ・Analytics Tools: Looker Studio, Tableau, Google Analytics ・CI/CD: Cloud Build, GitHub Actions, Argo CD ・Logging/Monitoring: Datadog Working Hours Full Flextime System *With No Core Time Job Requirements Required - 3+ years of experience in software development using Python - Practical experience building, evaluating, and improving machine learning or natural language processing models (e.g., recommendation systems, classification, regression, NLP) - Experience developing and operating web applications or APIs (language agnostic) - Development experience using public cloud platforms (GCP / AWS / Azure) - Experience collaborating with business stakeholders to align requirements, define specifications, and drive projects forward - Experience proactively involved in production environment operations (including incident response and improvements) - Experience designing and implementing models with an awareness of explainability and risk Preferred - Experience developing applications using LLM/generative AI (including prompt design, evaluation workflow design, and guardrail design) - Experience operating machine learning systems in production (including model monitoring, data drift detection, and retraining pipeline construction) - Experience using MLOps/GenAIOps tools (e.g., MLflow, Langfuse) - Experience developing and operating models for recommendation systems, anomaly detection, or fraud detection - Experience driving internal AI adoption or promoting AI tool implementation Ideal Applicants - Empathy with the company's mission and collaborate in a purpose-driven manner - Focus on achieving significant results as a team - Set priorities with the goal of maximizing business impact - Take ownership and proactively see projects through to completion - Embrace differing opinions, speak up without fear, and engage in logical discussions English Level None Japanese Level Business Level(JLPT Level 2 or N2)