データサイエンティスト/データアナリスト、正社員、600万円以上の転職・求人情報

求める人材: Roles & Responsibilities * Design and implement complex application features across frontend, backend, and AI workflow layers * Independently develop and maintain backend services and APIs using Python and FastAPI * Build frontend interfaces and interaction layers using React, Next.js/Remix, and Tailwind CSS * Implement real-time streaming workflows using Server-Sent Events (SSE) or similar technologies * Design and implement LLM-integrated applications, including business workflow automation and knowledge retrieval systems * Build and optimize Retrieval-Augmented Generation (RAG) pipelines, including advanced retrieval strategies, hybrid search, and re-ranking techniques * Develop and maintain evaluation loops to measure AI output quality, retrieval effectiveness, and guardrail compliance * Design and implement guardrails and control mechanisms to improve safety, reliability, and output consistency * Contribute to architecture decisions related to service decomposition, integration patterns, and scalability * Build and optimize data pipelines, data transformation workflows, and data quality validation mechanisms * Implement and optimize CI/CD pipelines, deployment automation, and infrastructure provisioning workflows * Ensure systems meet security requirements, including authentication, authorization, and access control enforcement * Implement observability standards including logging, monitoring, tracing, and alerting * Review code, mentor junior engineers, and enforce engineering quality standards * Translate business and product requirements into technical specifications and implementation plans * Troubleshoot complex issues across application, AI, and infrastructure layers Skills & Requirements Experience * 4 to 6 years of software development experience * Experience building production-grade software systems, including exposure to AI-enabled or data-driven systems * Proven ability to independently own features and contribute to architectural decisions Architecture & System Design * Strong understanding of microservices architecture patterns and service decomposition * Experience implementing Test Driven Development (TDD) and structured testing practices * Strong understanding of database design principles across SQL and NoSQL systems * Ability to design scalable, maintainable, and resilient application components Frontend Development * Strong experience in React development * Experience building responsive interfaces using Tailwind CSS * Familiarity with Next.js or Remix frameworks * Understanding of SSE (Server-Sent Events) for real-time communication and streaming interactions Backend Development * Strong hands-on experience with Python development * Strong expertise in FastAPI and modern API development practices * Strong understanding of REST API principles, service integration, and backend architecture * Experience building scalable backend workflows and asynchronous processing patterns AI / ML Engineering * Strong understanding of LLM integration patterns and AI application workflows * Hands-on experience implementing advanced RAG architectures * Experience with Hybrid Search and Re-ranking strategies for retrieval optimization * Experience designing and maintaining evaluation loops for model quality and response consistency * Experience implementing Guardrails for safe and reliable AI behavior Data Engineering * Experience in data exploration and profiling * Experience building and maintaining data pipelines * Understanding of data quality validation and data integrity practices * Familiarity with structured and semi-structured data handling patterns DevOps & Cloud Engineering * Strong working knowledge of Docker and Kubernetes * Experience implementing and maintaining CI/CD pipelines * Hands-on experience with Infrastructure-as-Code (Terraform) * Understanding of cloud-native deployment patterns and release management Security & Observability * Strong understanding of IAM, OAuth2, and secure API design * Familiarity with network policies and service security controls * Experience implementing monitoring and observability using Prometheus, Grafana, and OpenTelemetry Engineering Practices * Strong debugging and troubleshooting capability across application and AI layers * Strong understanding of testing strategies and engineering quality practices * Experience in collaborative development and version control workflows * Ability to document technical decisions, designs, and implementation patterns clearly Soft Skills * Strong ownership and accountability for delivery outcomes * Ability to communicate technical trade-offs and architecture decisions clearly * Strong collaboration and adaptability in cross-functional teams * Leadership capability in guiding junior engineers and supporting team delivery * Strong problem-solving mindset with structured scenario analysis * Ability to translate business requirements into technical implementation plans * Reliability mindset with focus on system stability and maintainability * Openness to feedback and continuous improvement Nice to Have * Experience with LLM orchestration frameworks such as LangChain or similar * Exposure to vector databases and semantic search systems * Experience working with cloud platforms (AWS, Azure, GCP) * Experience in AI-first product or platform engineering environments * Experience supporting enterprise-scale AI implementations * Trial period 3 months; salary and conditions unchanged during trial Working hours Fixed-hours system, 9:00–18:00, 60-min break, 8 working hours Holidays and leave Two full days off per week (Sat/Sun), public holidays, year-end/New Year, summer leave, 10 days annual paid leave after 6 months, condolence/celebration leave, maternity/childcare/nursing-care leave (with take-up record); [n] days off per year Salary Annual ¥6,000,000–¥12,000,000 paid in 12 instalments); set on experience and skills; no fixed overtime included, overtime paid separately in full Raise and bonus Raise once a year (April); bonus twice a year (June and December), subject to company results and individual evaluation Social insurance Full coverage: health insurance, employees' pension, employment insurance, workers' accident insurance; enrolled from date of hire in accordance with law Benefits Annual health check, certification support (exam and renewal fees), book allowance, external training and conference fees, company PC and monitor, GPU/cloud environment provided, casual dress Passive smoking Indoor smoking prohibited Reason for hiring Additional headcount to strengthen the AI product development team Selection process Document screening → first interview (online) → technical assignment or technical interview → final interview → offer; as fast as 2 weeks from application

求める人材: Roles & Responsibilities * Lead end-to-end delivery of AI/ML, data platform, and cloud modernization initiatives across engineering, platform, and business teams using Agile, Scrum, SAFe, or hybrid delivery models * Apply agile delivery practices including iteration planning, backlog refinement, sprint execution, and PI planning (where applicable) * Partner closely with architects, tech leads, and engineers to translate technical designs into executable delivery plans * Own and maintain integrated delivery plans covering architecture, development, data, infrastructure, security, and release activities * Drive technical dependency management across application, data, infrastructure, and integration layers * Actively participate in architecture, design, and technical planning discussions to identify delivery risks, constraints, and trade-offs early * Manage release planning and execution across CI/CD pipelines and Dev/Test/Prod environments * Identify, assess, and mitigate technical risks related to scalability, data quality, security, performance, and environment readiness * Ensure delivery alignment with SDLC, agile, and hybrid delivery models * Provide clear, technically grounded delivery status, risks, and recommendations to senior technical and business stakeholders * Support budget tracking, cost control, and vendor coordination, ensuring delivery commitments align with commercial constraints * Ensure adherence to governance, compliance, and audit requirements throughout the delivery lifecycle (GDPR, SOC2, ISO) Skills & Requirements * 4 to 8 years of experience in technical project or delivery management * Proven experience managing AI/ML, data platform, or cloud modernization programs * Strong understanding of SDLC for data, AI, and platform-based systems * Working knowledge of cloud platforms, data pipelines, AI/ML workflows, and system integration patterns * Experience with CI/CD pipelines, release management, and multi-environment delivery (Dev/Test/Prod) * Strong capability in technical dependency management, risk assessment, and milestone planning * Experience with budgeting, cost tracking, and vendor management in enterprise programs * Familiarity with compliance, audit, and governance frameworks such as GDPR, SOC2, and ISO * Ability to engage credibly with senior engineers, architects, and platform teams on technical topics * Strong stakeholder management and executive-level written and verbal communication * High ownership, accountability, and ability to make decisions under ambiguity

求める人材: Roles & Responsibilities * Engage directly with customers to understand business challenges, technical requirements, and operational constraints * Translate customer requirements into solution designs, technical workflows, and implementation plans * Design, develop, and deploy production-grade applications using Python, JavaScript, or related technologies * Build and integrate LLM-powered applications, including conversational systems, automation workflows, and knowledge-based systems * Design and implement Retrieval-Augmented Generation (RAG) pipelines, including document ingestion, embedding strategies, retrieval optimization, and response orchestration * Build and manage agent-based architectures, including task orchestration, tool integration, and execution flows * Design and maintain evaluation frameworks to measure model quality, retrieval effectiveness, and output reliability * Implement and manage MLOps/LLMOps pipelines covering deployment, monitoring, versioning, rollback, and lifecycle management * Develop and deploy applications in cloud environments such as AWS, Azure, or GCP * Collaborate with data engineers, architects, and technical leads to integrate AI workflows into enterprise systems * Identify technical risks and implementation bottlenecks, proposing mitigation strategies proactively * Balance rapid prototyping with production-readiness, ensuring quality, scalability, and maintainability * Support optimization of delivery workflows by leveraging AI tools to improve engineering productivity and operational efficiency Skills & Requirements Experience * Minimum 5 years of experience in software engineering, technical implementation, or related technical delivery roles * Proven experience driving projects with direct client engagement and stakeholder management * Experience working in fast-paced, ambiguous delivery environments with strong ownership and execution capability Application Engineering * Strong hands-on development experience using Python and/or JavaScript * Experience building production-grade backend services, APIs, and application workflows * Strong understanding of software engineering fundamentals including modular design, testing, and maintainability * Experience integrating frontend and backend components for end-to-end solution delivery Applied AI Engineering * Demonstrated experience building or implementing applications leveraging Large Language Models (LLMs) and Generative AI technologies * Practical experience designing and implementing Retrieval-Augmented Generation (RAG) workflows * Experience in agent design, orchestration logic, and tool-based execution patterns * Experience building evaluation frameworks for model validation, retrieval quality, and output consistency * Understanding of prompt engineering, model behavior optimization, and AI system reliability Cloud & Platform Engineering * Experience building and deploying systems in cloud environments (AWS, GCP, Azure) * Experience with containerized deployment and cloud-native architecture patterns * Understanding of deployment automation, CI/CD pipelines, and infrastructure provisioning * Familiarity with application scalability, resilience, and cloud cost optimization MLOps / LLMOps * Experience designing and operating MLOps and/or LLMOps pipelines * Understanding of model lifecycle management including deployment, versioning, monitoring, and rollback * Experience implementing observability for AI systems, including performance and quality monitoring Customer Delivery & Stakeholder Engagement * Strong ability to engage with customers to clarify requirements, align expectations, and drive delivery decisions * Ability to explain complex technical concepts to business and non-technical stakeholders * Experience balancing customer priorities with technical feasibility and delivery constraints Soft Skills * Strong problem-solving orientation with a customer-first mindset * Ability to balance hands-on coding with customer-facing engagement * Strong decision-making capability under ambiguity * Ability to maintain delivery speed without compromising quality * Strong ownership and accountability for delivery outcomes * Ability to remain composed and effective in high-pressure delivery environments Nice to Have * Experience implementing large-scale enterprise systems * Experience in data security, governance, and access control design * Experience working in startup or new business environments * Experience collaborating with global or distributed teams * Strong English communication skills * Experience with observability tools and operational monitoring for AI systems