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
