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Microsoft

Builds workplace software, PCs and cloud services

Solution Architect - Data & AI

Implementation & Technical Account ManagementConfirmed live in the last 24 hours
Full-timeThailandNo salary listedIn-person

About the Job

Requirements

  • A bachelor's degree in Computer Science, Engineering, Data Science, Information Technology, Business, or a related field and 6+ years of relevant solution architecture, technical presales, Data & AI, cloud architecture, consulting, or technology delivery experience, or equivalent experience.
  • Experience shaping and architecting enterprise Data, Analytics, AI, Generative AI, or cloud transformation solutions.
  • Experience leading customer-facing technical discovery, architecture workshops, solution design, and technical decision-making for complex enterprise opportunities.
  • Good knowledge of modern Data & AI architectures, including data engineering, lakehouse, analytics, data governance, semantic and vector search, machine learning, retrieval-augmented generation (RAG), Generative AI, and Agentic AI.
  • Experience designing AI agents or agentic solutions incorporating grounding, tool/function calling, reusable skills, workflows, orchestration, memory, evaluation, and human oversight.
  • Experience with modern cloud and Data & AI technologies, preferably Microsoft Azure, Microsoft Fabric, Azure AI Foundry, Azure OpenAI, Azure AI Search, Azure Databricks, and/or Power BI.
  • Experience translating business requirements into architecture strategies, roadmaps, solution designs, delivery approaches, estimates, risks, and measurable success criteria.
  • Experience taking solutions from envisioning and proof of concept through secure, scalable production deployment and adoption.
  • Understanding of security, identity, data governance, privacy, Responsible AI, observability, resilience, regulatory compliance, and cost optimization.
  • Ability to independently lead complex solution architecture workstreams and influence decisions across business, sales, engineering, delivery, and partner teams.

Responsibilities

  • Lead solution envisioning and shaping by engaging with customer executives, business sponsors, enterprise architects, security teams, and engineering leaders to understand priorities, identify opportunities, and define outcome-based Data & AI solutions.
  • Define the solution architecture by creating and documenting the architecture vision, value proposition, target architecture, transition roadmap, architecture decisions, requirements, constraints, assumptions, dependencies, and risks.
  • Architect modern Data & AI platforms, including enterprise data platforms, lakehouse architectures, data engineering, analytics, real-time data, governance, search, machine learning, and AI solutions using Microsoft Azure, Microsoft Fabric, Databricks, and related technologies.
  • Architect Generative and Agentic AI solutions, including architectures for Generative AI applications, RAG, enterprise knowledge, AI agents, multi-agent systems, reusable skills, tool integration, orchestration, memory, evaluation, and human-in-the-loop controls.
  • Shape complex opportunities by leading technical discovery, solution modelling, architecture workshops, demonstrations, proofs of concept, estimation, and solution proposals in collaboration with sales, account, consulting, engineering, and partner teams.
  • Connect architecture to business value by translating technology choices into business outcomes, cloud adoption, consumption plans, operating efficiencies, risk reduction, and measurable value-realization objectives.
  • Provide architecture governance by establishing architecture principles, standards, decision processes, and quality gates across design, build, testing, deployment, production, and optimization.
  • Drive security and Responsible AI by embedding security, identity, privacy, data governance, regulatory compliance, Responsible AI, observability, resilience, and operational controls into the solution architecture.
  • Guide production delivery by providing architectural direction to consultants, engineers, data scientists, and partners while resolving complex design issues and managing technical dependencies and risks.
  • Apply AI-first methods using copilots, agents, automation, and AI-assisted architecture techniques to accelerate discovery, design, documentation, risk assessment, estimation, and architecture validation.
  • Scale architectural impact by reusing and contributing reference architectures, delivery intellectual property, solution patterns, accelerators, architecture decision records, and lessons learned across customer engagements.
  • Provide technical thought leadership by mentoring architects and technical professionals, communicating architecture and business value to senior stakeholders, and contributing to the broader Data & AI technical community.

Desired Qualifications

  • 12+ years of relevant solution architecture, technical presales, enterprise Data & AI, cloud transformation, consulting, or solution delivery experience.
  • Demonstrated experience leading end-to-end solution shaping and technical presales, from opportunity discovery and business-value definition through proposal, proof of concept, delivery governance, and production adoption.
  • Deep architecture expertise across Microsoft Azure, Microsoft Fabric, Databricks, data platforms, Generative AI, large language models (LLMs), RAG, agentic systems, and enterprise integration.
  • Experience with enterprise-scale data modernization, lakehouse, analytics, AI platform, multi-cloud, or migration programs.
  • Experience designing and governing multi-agent architectures, enterprise knowledge solutions, AI platforms, or intelligent process transformation.
  • Ability to model solution options, articulate trade-offs, estimate cost and consumption, identify risks, and present recommendations to executive stakeholders.
  • Experience defining reusable reference architectures, solution patterns, technical standards, architecture decision records, and delivery accelerators.
  • Experience providing technical governance and quality assurance across multidisciplinary customer, Microsoft, and partner delivery teams.
  • Relevant technical certifications aligned to the solution area, such as Azure Solutions Architect, Fabric Analytics Engineer, Azure AI Engineer, Data Engineer, or Security, or equivalent certifications.
  • Architecture or delivery methodology certifications such as TOGAF, Agile, Scrum, DevOps, PMP, or Change Management.
  • Demonstrated ability to mentor architects and engineers, lead technical communities, and contribute thought leadership across Data & AI.

About the Company

Microsoft

Builds workplace software, PCs and cloud services

Microsoft builds workplace software, operating systems and cloud infrastructure for consumers, businesses and government agencies, from small organizations to global enterprises. Microsoft 365 combines Word and Excel with Teams communication and Copilot AI features, while Windows runs PCs and Surface supplies the company's own computers. Azure rents computing capacity, storage and databases to build and run web applications. Microsoft also sells Xbox consoles and games, collecting revenue through software licenses, subscriptions, usage charges and product sales. Founded in 1975 by Bill Gates and Paul Allen, Microsoft is headquartered in Redmond, Washington.

Company size
10,001+
Company stage
IPO
Headquarters
Redmond, WA
Founded
1975

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