Digital Cloud & AI Solution Engineer – Innovative AI Applications at Microsoft

Enhanced Job Description

📍 Job Overview

Job Title: Digital Cloud & AI Solution Engineer – Innovative AI Applications
Company: Microsoft
Location: Bangkok, Krung Thep Maha Nakhon, Thailand
Job Type: Full-Time
Category: Web Technology - AI Applications
Date Posted: July 4, 2025

🚀 Role Summary

As a Digital Cloud & AI Solution Engineer (DSE) at Microsoft, you will play a pivotal role in helping enterprise AI developers unlock the full potential of Microsoft’s AI-powered stack across every stage of the development lifecycle. You will collaborate closely with engineering leaders and platform teams to accelerate AI Foundry, Cloud & AI, and Responsible AI through hands-on engagements like Proof of Concepts, hackathons, and architecture workshops. This opportunity allows you to accelerate your career growth, develop deep business acumen, hone your technical skills, and become adept at solution design and deployment. You will guide customers through secure, scalable solution design, influence technical decisions, and accelerate AI applications development into their deployment workflows, helping them modernize their applications and realize the full value of Microsoft’s AI platform.

💻 Primary Responsibilities

Accelerate AI Adoption: Work closely with enterprise AI developers to modernize their applications and adopt AI-powered solutions across the development lifecycle.
Solution Design & Deployment: Guide customers through secure, scalable solution design and deployment, ensuring their applications leverage AI effectively and efficiently.
Technical Advisory: Provide expert guidance on AI technologies, best practices, and architectural decisions to shape customers’ technical roadmaps.
Collaboration & Knowledge Sharing: Collaborate with engineering teams, platform specialists, and customer developers to deliver successful outcomes and foster a culture of continuous learning.
Innovation & Problem-Solving: Drive innovation by staying up-to-date with emerging AI technologies, trends, and industry best practices, and applying them to solve customers’ unique challenges.

🎓 Skills & Qualifications

Education: Bachelor's degree in Computer Science, AI, or a related field. Relevant master's degree is a plus.

Experience: 2-5 years of experience in AI development, cloud technologies, or a related field. Proven track record in solution design, architecture, or technical consulting is preferred.

Required Skills:

Proficiency in AI development and cloud technologies
Strong problem-solving skills and analytical thinking
Excellent communication and collaboration skills
Experience with AI frameworks, libraries, and tools (e.g., TensorFlow, PyTorch, Azure AI)
Familiarity with cloud platforms and infrastructure (e.g., Azure, AWS, GCP)
Knowledge of software development lifecycle and Agile methodologies
Experience with solution design, architecture, and deployment

Preferred Skills:

Experience with AI ethics, fairness, and responsible AI practices
Familiarity with AI deployment, monitoring, and maintenance
Knowledge of AI-specific security best practices
Experience with AI project management and team leadership

📊 Web Portfolio & Project Requirements

Portfolio Essentials:

A portfolio showcasing your AI projects, with a focus on solution design, architecture, and deployment
Live demos or videos demonstrating your AI applications and their functionality
Documentation detailing your AI project’s architecture, data processing pipelines, and deployment strategies

Technical Documentation:

Code quality, commenting, and documentation standards for AI projects
Version control, deployment processes, and server configuration best practices
Testing methodologies, performance metrics, and optimization techniques specific to AI applications

💵 Compensation & Benefits

Salary Range: 600,000 - 1,200,000 THB per year (Region-specific, based on experience level and market standards)

Benefits:

Comprehensive health insurance and wellness programs
Retirement savings plans and financial planning resources
Generous vacation and time-off policies
Employee stock purchase plan and equity compensation opportunities
Learning and development opportunities, including AI-specific certifications and training
Flexible work arrangements, including remote work and hybrid options

Working Hours: 40 hours per week, with flexible scheduling for project deadlines and maintenance windows

🎯 Team & Company Context

Company Culture: Microsoft fosters a culture of innovation, opportunity, and inclusivity. Here, you will be part of a diverse, high-performing, and customer-obsessed team where collaboration, connection, and continuous learning fuel everything they do.

Team Structure:

Work closely with engineering leaders, platform teams, and customer developers to deliver successful outcomes
Collaborate with cross-functional teams, including design, marketing, and business stakeholders
Engage with a global network of AI and cloud professionals to drive innovation and best practices

Development Methodology:

Agile methodologies and sprint planning for AI projects
Code review, testing, and quality assurance practices for AI applications
Deployment strategies, CI/CD pipelines, and server management for AI solutions

📈 Career & Growth Analysis

AI Career Level: As a Digital Cloud & AI Solution Engineer, you will operate at a senior individual contributor level, driving strategic AI initiatives and influencing technical roadmaps.

Reporting Structure: You will report directly to the AI Solution Engineering manager, collaborating with cross-functional teams and stakeholders.

Technical Impact: Your work will have a significant impact on enterprise AI developers’ ability to modernize their applications, adopt AI-powered solutions, and drive innovation in their development lifecycle.

Growth Opportunities:

Career Progression: Advance to senior roles, such as AI Solution Architecture or AI Technical Lead, as you develop deep business acumen and technical expertise.
Technical Skill Development: Expand your AI and cloud technology skills through hands-on projects, workshops, and continuous learning opportunities.
Leadership & Mentoring: Mentor junior AI developers and contribute to the growth of Microsoft’s AI community.

🌐 Work Environment

Office Type: Flexible work arrangements, including remote work and hybrid options, to balance work-life integration and collaboration.

Office Location: Bangkok, Krung Thep Maha Nakhon, Thailand, with remote work options available.

Workspace Context:

Collaborative workspace with dedicated AI development resources and tools
Access to Microsoft’s global network of AI and cloud professionals for knowledge sharing and best practice exchange
Flexible work schedules to accommodate project deadlines and maintenance windows

📄 Application & Technical Interview Process

Interview Process:

Phone Screen: A brief phone call to discuss your AI background, experience, and career goals.
Technical Deep Dive: A detailed technical conversation focusing on your AI portfolio, project experience, and problem-solving skills.
Behavioral & Cultural Fit: An interview to assess your collaboration skills, cultural fit, and alignment with Microsoft’s values.
Final Interview: A meeting with the hiring manager and key stakeholders to discuss your fit for the role and next steps.

Portfolio Review Tips:

Highlight your AI projects’ architecture, solution design, and deployment strategies
Include live demos or videos showcasing your AI applications and their functionality
Emphasize your AI project’s impact, user experience, and performance optimization techniques

Technical Challenge Preparation:

Brush up on your AI development skills, focusing on solution design, architecture, and deployment
Familiarize yourself with Microsoft’s AI stack, including Azure AI, AI Foundry, and Responsible AI
Prepare for AI-specific problem-solving exercises and architecture discussions

ATS Keywords: (Comprehensive list provided at the end of the document)

🛠 Technology Stack & Web Infrastructure

AI Development Tools:

Azure AI: Microsoft’s comprehensive AI platform for building, deploying, and managing AI solutions
AI Foundry: A cloud-based development environment for building, testing, and deploying AI models
Responsible AI: A framework for building ethical, transparent, and accountable AI systems

Cloud & Infrastructure Tools:

Azure: Microsoft’s global cloud platform for building, testing, and managing applications and services
Kubernetes: An open-source platform for automating deployment, scaling, and management of containerized applications
Azure DevOps: A set of services for automating the deployment and management of applications in the cloud

AI Development Methodologies:

Agile methodologies for AI project management and development
CI/CD pipelines for automated AI model deployment and testing
MLOps (Machine Learning Operations) for streamlining AI model deployment and management

👥 Team Culture & Values

AI Development Values:

Innovation: Drive continuous innovation in AI development and deployment to stay ahead of emerging trends and technologies
User Experience: Prioritize user experience and accessibility in AI application design and development
Performance Optimization: Focus on AI model performance, efficiency, and scalability to meet enterprise needs
Code Quality: Maintain high code quality standards, including commenting, documentation, and version control
Collaboration: Foster a culture of collaboration, knowledge sharing, and continuous learning among AI developers and stakeholders

Collaboration Style:

Cross-Functional Integration: Work closely with designers, marketers, and business stakeholders to deliver AI solutions that meet user needs and drive business impact
Code Review Culture: Encourage code review practices to ensure high-quality AI code and knowledge sharing
Mentoring & Knowledge Sharing: Foster a culture of mentoring and knowledge sharing to help junior AI developers grow and succeed

🛡 Challenges & Growth Opportunities

AI Development Challenges:

AI Model Complexity: Design and deploy complex AI models that meet enterprise needs and scale efficiently
Data Privacy & Security: Ensure AI model security, privacy, and compliance with enterprise data protection regulations
AI Model Interpretability: Develop AI models that are interpretable, explainable, and transparent to enterprise users and stakeholders
AI Model Maintenance: Manage and maintain AI models in production, ensuring their performance, accuracy, and reliability over time

Learning & Development Opportunities:

AI Technology Specialization: Deepen your expertise in specific AI technologies, frameworks, or industry verticals to drive innovation and impact
AI Leadership Development: Develop your leadership skills to mentor junior AI developers, drive AI projects, and influence AI strategy
AI Community Engagement: Engage with Microsoft’s global AI community to learn, collaborate, and drive AI best practices and innovation

💡 Interview Preparation

Technical Questions:

AI Development Fundamentals: Prepare for questions about AI development fundamentals, including AI frameworks, libraries, and tools
AI Architecture & Design: Brush up on your AI architecture and design skills, focusing on solution design, deployment, and scalability
AI Problem-Solving: Practice AI problem-solving exercises and architecture discussions to demonstrate your analytical thinking and problem-solving skills

Company & Culture Questions:

Microsoft’s AI Strategy: Research Microsoft’s AI strategy, focusing on AI Foundry, Azure AI, and Responsible AI
AI Industry Trends: Stay up-to-date with AI industry trends, emerging technologies, and best practices
AI Ethics & Responsibility: Familiarize yourself with AI ethics, fairness, and responsible AI practices, and be prepared to discuss their importance in AI development

Portfolio Presentation Strategy:

AI Project Highlights: Highlight your AI projects’ architecture, solution design, and deployment strategies
AI Project Impact: Emphasize your AI project’s impact, user experience, and performance optimization techniques
AI Project Challenges: Discuss the challenges you faced in your AI projects and how you overcame them to deliver successful outcomes

📌 Application Steps

To apply for this AI Solution Engineer position:

Submit Your Application: Click the 'Apply' button on the job listing page.
Prepare Your Portfolio: Highlight your AI projects’ architecture, solution design, and deployment strategies, and include live demos or videos showcasing your AI applications and their functionality.
Optimize Your Resume: Tailor your resume to emphasize your AI development skills, experience, and achievements, focusing on AI-specific keywords and ATS optimization.
Prepare for Technical Interviews: Brush up on your AI development skills, focusing on solution design, architecture, and deployment, and prepare for AI-specific problem-solving exercises and architecture discussions.
Research Microsoft’s AI Strategy: Familiarize yourself with Microsoft’s AI strategy, focusing on AI Foundry, Azure AI, and Responsible AI, and be prepared to discuss their relevance to the role and your AI development experience.

Digital Cloud & AI Solution Engineer – Innovative AI Applications