Analytics Solutions Architect

Amazon Amazon · Big Tech · 13, Japan +1 · Solutions Architect

Specialist Solutions Architect focused on designing and building agent-ready data platforms that leverage generative AI, RAG, semantic search, and real-time streaming for customer analytics, search, and streaming workloads. The role involves creating reference architectures and providing guidance on AI/ML integration and multimodal data utilization.

What you'd actually do

  1. Provide customers with best practices for building and operating analytics, search, and streaming workloads.
  2. Partner with customers to design agent-ready data platforms — foundations that enable AI agents to autonomously search, process, and analyze data to support decision-making.
  3. Design and build cloud-native and generative-AI-native reference architectures with your own hands, and share them broadly with the technical community through white papers, workshops, blogs, and more.
  4. Continuously provide feedback to shape the roadmap for AWS analytics, search, streaming, and generative AI services.

Skills

Required

  • Big data processing technologies (Hadoop, Apache Spark, etc.)
  • Stream processing (Apache Kafka, Amazon Kinesis, Apache Flink, etc.)
  • Search platforms (OpenSearch, Elasticsearch, vector search, semantic search)
  • Data warehouse technical architectures
  • ETL
  • Reporting/analytics tools
  • Generative AI powered data architectures (RAG, semantic search, vector databases, LLM orchestration, AI agent-driven data pipeline automation)
  • Building and nurturing relationships with internal and external stakeholders
  • Fluent spoken and written Japanese (JLPT N1 or equivalent)

Nice to have

  • 3+ years of experience in cloud architecture and solution implementation
  • AWS Associate-level certification
  • Generative AI / AI agent platforms
  • AI/ML
  • Databases
  • Governance
  • Storage
  • Customer-facing role experience
  • English communication skills

What the JD emphasized

  • generative AI
  • AI agents
  • data platforms
  • analytics
  • search
  • streaming
  • RAG
  • semantic search
  • vector databases
  • LLM orchestration
  • AI agent-driven data pipeline automation

Other signals

  • designing agent-ready data platforms
  • AI agents autonomously search, process, and analyze data
  • semantic search powered by generative AI
  • RAG-based insight generation
  • convergence of real-time streaming with AI
  • AI/ML integration
  • multimodal data utilization