Generative AI Engineer

Generative AI Engineer

Role Overview

• Design and deliver generative AI applications from the ground up, including context-augmented paradigms such as RAG/CAG and intelligent agent orchestration.
• Prioritize building operable, measurable, and scalable production-grade systems on Azure, ensuring performance, compliance, and cost optimization.

Key Responsibilities

• Design and implement RAG/CAG-based application architectures: data ingestion, chunking and embeddings, retrieval and re-ranking, context injection, and response generation.
• Build and orchestrate multi-agent workflows: task decomposition and tool invocation.
• Use frameworks such as LangChain/LangGraph to implement end-to-end pipelines and integrate services (APIs, queues, event-driven).
• Set up AI and infrastructure services on Azure (preferred) or AWS/GCP (vector search, inference services, model hosting, monitoring and logging).
• Establish evaluation and monitoring systems: offline/online evaluation, A/B testing, data drift and data quality monitoring, cost and latency optimization.
• Implement prompt/tool/memory design and versioning to ensure reproducibility and maintainability.
• Drive engineering and automation: CI/CD and environment management.
• Produce technical documentation and best practices; support the evolution from PoC to production.

Requirements (Must-Haves)

• Bachelor's degree in computer science or related field.
• 2+ years of relevant work experience.
• Proficient written and spoken Japanese and strong written English; able to independently communicate with Japanese clients in Japanese.
• Strong communication, documentation, and interpersonal skills.
• Solid generative AI development skills; familiar with context-augmented generation paradigms such as RAG/CAG and common design patterns (chunking, embedding selection, vector indexing and re-ranking, context length/window management, cache augmentation).
• Hands-on agent development experience; understanding of task planning, tool invocation, memory/state, and LangGraph semantics (graph state, nodes, edges).
• Familiar with the LangChain/LangGraph ecosystem; able to implement custom chains, tools, executors, and callback-based monitoring.
• Familiar with Azure AI services and configurations: Azure OpenAI, Azure AI Search (vector retrieval), Bing Search grounding, etc.
• Strong software engineering skills: at least one primary language (Python/TypeScript), API design, unit/integration testing, performance tuning.

Nice-to-Haves

• Experience using AI-assisted development tools (Claude Code, Agent Skills, Cursor, Copilot, OpenAI o3) with demonstrated impact.
• Experience with Power Platform (Copilot Studio, Power Apps, etc.) preferred.
• Experience in machine learning/data analysis: feature engineering, statistical analysis, model selection and hyperparameter tuning, A/B test design.
• Familiarity with other cloud platforms: AWS (Bedrock), GCP (Vertex AI, Big Query, Cloud Run).
• Strong understanding of the software development lifecycle; Agile experience preferred.
• Prior work experience in Japan or fluent spoken English is a plus.