Data and AI Solution Architect

Microsoft Microsoft · Big Tech · Singapore +1 · Solution Architecture

This role focuses on designing and leading end-to-end enterprise data, GenAI, Copilot, and agentic AI architectures. The Solution Architect translates business outcomes into scalable, secure, and governed solutions, owns data platform design for AI readiness, leads data migration and modernization, architects cross-cloud data integration, defines GenAI solution patterns (prompt orchestration, RAG, embeddings), and leads architecture for Copilot and AI-augmented applications, including agentic AI architectures.

What you'd actually do

  1. Design and lead end‑to‑end enterprise data, GenAI, Copilot, and agentic AI architectures, translating business outcomes into scalable, secure, and governed solutions across cloud data platforms and AI services.
  2. Own data platform design (lakehouse/data lake/warehouse, streaming, analytics, semantic models) to ensure the enterprise data estate is AI‑ready (quality, lineage, governance, observability).
  3. Lead data migration and modernization from on‑premises environments to cloud, including planning and executing migrations with minimal disruption, and aligning migration choices to modernization goals.
  4. Architect and drive cross‑cloud / multi‑cloud data integration and migration scenarios (e.g., AWS/GCP/Azure), including federated analytics approaches and unified governance across clouds where required.
  5. Define GenAI solution patterns, including prompt orchestration, embeddings, vector search, retrieval‑augmented generation (RAG), and grounding strategies that connect LLMs to enterprise data and systems.

Skills

Required

  • GenAI
  • Copilot
  • agentic AI architectures
  • enterprise data architectures
  • cloud data platforms
  • AI services
  • data platform design
  • data migration
  • data modernization
  • cross-cloud / multi-cloud data integration
  • prompt orchestration
  • embeddings
  • vector search
  • retrieval-augmented generation (RAG)
  • grounding strategies
  • AI-augmented applications
  • enterprise architecture
  • security standards
  • governance

Nice to have

  • lakehouse
  • data lake
  • data warehouse
  • streaming analytics
  • semantic models
  • federated analytics
  • AWS
  • GCP
  • Azure

Other signals

  • design and lead end‑to‑end enterprise data, GenAI, Copilot, and agentic AI architectures
  • translate business outcomes into scalable, secure, and governed solutions
  • architect and drive cross‑cloud / multi‑cloud data integration and migration scenarios
  • define GenAI solution patterns, including prompt orchestration, embeddings, vector search, retrieval‑augmented generation (RAG), and grounding strategies
  • lead architecture for Copilot and AI‑augmented applications
  • design and govern agentic AI architectures