Junior AI Engineer – GenAI & Agentic AI Platform
Hybrid · Tokyo, Tokyo, Japan
Job Summary
Junior AI Engineer — GenAI & Agentic AI Platform responsible for designing and delivering production-grade GenAI and Agentic AI solutions across Copilot Studio, ChatGPT Enterprise, and AWS Bedrock. Responsibilities include building GenAI pipelines (RAG, LLM-powered workflows), developing multi-agent AI systems (LangGraph, AutoGen, Agents for Bedrock), maintaining medallion architecture on Databricks/Delta Lake for structured and unstructured data, implementing Informatica IDMC pipelines for ingestion, quality, MDM, and lineage, and deploying Microsoft Copilot Studio copilots and ChatGPT Enterprise at scale with governance and data privacy considerations. Collaboration with pharma clients in Japan, contributing to governance, prompt engineering, and memory/planning components, and leveraging vector databases for retrieval. Required and preferred skills span Databricks, Informatica IDMC, Python, LangChain/LangGraph, NLP/ OCR, embedding generation, and familiarity with pharma data platforms; experience across Microsoft Copilot Studio, OpenAI API, and AWS Bedrock is valued.
Required Qualifications
- 3-4 years in AI/ML engineering, data engineering, or applied AI with at least 1 year on GenAI or LLM-based production systems
- Hands-on experience with at least two of: Microsoft Copilot Studio, ChatGPT Enterprise / OpenAI API, AWS Bedrock — with working familiarity across all three
- Proven experience designing Agentic AI systems: multi-agent orchestration, tool-use patterns, memory management, and planning with LangGraph, AutoGen, or equivalent
- Deep proficiency with Databricks (Delta Lake, MLflow, Unity Catalog) and medallion architecture for structured and unstructured data
- Hands-on Informatica IDMC experience — CDI, CAI, data quality rules, MDM, or data lineage workflows
- Strong Python skills; proficiency with LangChain, LangGraph, LlamaIndex, or similar AI orchestration frameworks
- Experience processing unstructured data: document parsing, NLP pipelines, OCR, or embedding generation
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