Junior AI Engineer – GenAI & Agentic AI Platform
Axtria, Inc.19 days ago
Tokyo, JapanEntry Level
Responsibilities
- Design and deploy RAG pipelines, LLM-powered workflows, and enterprise AI assistants across Microsoft Copilot Studio, ChatGPT Enterprise, and AWS Bedrock.
- Build multi-agent systems using LangGraph, AutoGen, and Agents for Bedrock with tool use, memory, and multi-step planning.
- Develop Databricks and Delta Lake medallion architectures for structured and unstructured pharma data.
- Implement Informatica IDMC pipelines for ingestion, data quality, master data management, lineage, and cloud/on-premises integration.
- Build Copilot Studio copilots, custom connectors, Power Platform workflows, and Microsoft Teams deployments.
- Deploy ChatGPT Enterprise with prompt governance, usage policies, API integrations, and data privacy controls.
- Use AWS Bedrock foundation model APIs, knowledge bases, Agents for Bedrock, and Guardrails for responsible AI.
- Build semantic retrieval and vector search layers using Pinecone, OpenSearch, Azure AI Search, and Bedrock Knowledge Bases.
- Define data governance, cataloguing, and lineage standards through Informatica IDMC and Databricks Unity Catalog.
- Conduct requirements workshops, solution demonstrations, and delivery reviews with pharma clients in Japan in Japanese.
- Champion agent safety, guardrails, model observability, and prompt governance across deployments.
Requirements
- 3–4 years of experience in AI/ML engineering, data engineering, or applied AI, including at least 1 year with production GenAI or LLM-based systems.
- Hands-on experience with at least two of Microsoft Copilot Studio, ChatGPT Enterprise/OpenAI API, and AWS Bedrock, with working familiarity across all three.
- Experience designing agentic AI systems involving multi-agent orchestration, tool use, memory management, and planning with LangGraph, AutoGen, or equivalent.
- Deep proficiency with Databricks, Delta Lake, MLflow, Unity Catalog, and medallion architecture.
- Hands-on Informatica IDMC experience, including CDI, CAI, data quality rules, MDM, or data lineage workflows.
- Strong Python skills and proficiency with LangChain, LangGraph, LlamaIndex, or similar AI orchestration frameworks.
- Experience processing unstructured data through document parsing, NLP pipelines, OCR, or embedding generation.
- Working knowledge of pharma functions such as commercial operations, R&D, sales force analytics, or medical affairs is preferred.
- Experience with Veeva CRM, IQVIA, Symphony Health, or equivalent pharma data platforms is preferred.
- Cloud certifications such as AWS ML Specialty, Solutions Architect, Azure AI Engineer, or Databricks certifications are preferred.
- Familiarity with Copilot Studio governance, Power Automate flows, Microsoft 365 Copilot extensibility, AWS SageMaker, Azure OpenAI Service, or Azure Data Factory is preferred.
Benefits
- Tokyo hybrid work arrangement with 3 days onsite.
- Opportunity to deliver GenAI and agentic AI solutions across pharma and life sciences client environments.
- Engagement with Microsoft, OpenAI, and AWS AI ecosystems and enterprise-scale responsible AI initiatives.
Tech Stack
Categories
AI ApplicationsData Engineering