At a Glance
- Tasks: Join Microsoft as a Cloud Solution Architect to drive AI solutions and customer success.
- Company: Microsoft empowers customers with innovative technology and exceptional experiences.
- Benefits: Enjoy flexible remote work, industry-leading healthcare, educational resources, and generous time off.
- Why this job: Accelerate your career in AI while making a real impact on customer outcomes.
- Qualifications: Bachelor's degree in tech or related field; expertise in Azure AI and cloud technologies required.
- Other info: Work from home up to 100% and engage with cutting-edge AI technologies.
The predicted salary is between 54000 - 84000 £ per year.
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Client:
Microsoft
Location:
Job Category:
Other
EU work permit required:
Yes
Job Reference:
77dc6a7810cb
Job Views:
7
Posted:
03.03.2025
Expiry Date:
17.04.2025
Job Description:
Overview
With over 17,000 employees worldwide, the mission of the Customer Experience & Success (CE&S) organization is to empower customers to accelerate business value through differentiated customer experiences that leverage Microsoft’s products and services, ignited by our people and culture. Come join CE&S and help us build a future where customers achieve their business outcomes faster with technology that does more.
The Global Customer Success (GCS) organization is leading the effort to create the desired customer experience through support offer creation, driving digital transformation across our tools, and delivering operational excellence across CE&S.
As a Cloud Solution Architect aligned to the Azure AI platform for Microsoft’s Customer Experience & Success (CE&S) organization, you will enable customers to achieve their outcomes based on their investments in Microsoft technology. Leveraging your Microsoft Azure Artificial Intelligence (AI) and Machine Learning (ML) technical subject matter expertise, you will lead technical conversations with customers and Microsoft colleagues, driving value to their organization. This is a hands-on role that includes accelerating customer adoption by building Generative AI solutions and identifying resolutions to unblock customer success projects. You will also drive product influence with Engineering through technical feedback and increase technical intensity with the Field teams. This opportunity will allow you to accelerate your career growth, honing your technical and programme management skills, and deepening your cloud expertise.
This role is flexible in that you can work up to 100% from home.
Qualifications
Required/Minimum Qualifications:
- Bachelor’s degree in computer science, Information Technology, Engineering, Business or related field AND experience in cloud/infrastructure technologies, information technology (IT) consulting/support, systems administration, network operations, software development/support, technology solutions, practice development, architecture, and/or Business Applications consulting OR equivalent experience.
- Domain Expertise in Azure AI Areas: Deep domain expertise in one of the Azure AI specific areas, such as Cognitive Services, Machine Learning, Azure OpenAI and CoPilot OR hands-on experience working with the respective products at the expert level.
- Breadth of technical experience and knowledge in foundational security, foundational AI, architecture design, with depth / Subject Matter Expertise in one or more of the following:
- Core AI & ML Concepts: Familiarity with AI & ML foundational knowledge of concepts like Prompt Engineering, compute systems (GPU & FPGA), popular frameworks (TensorFlow & PyTorch), and tools (Jupyter notebooks & VS Code).
- Generative AI and Responsible AI: Knowledge of current and emerging AI technology, including Generative AI technology applications and use cases (including, but not limited to, Large Language Models) and Foundational models toolsets. Understanding of Responsible AI practice including ethical considerations, bias mitigation, and fairness.
- Architecting Enterprise-Grade Solutions: The ability to create and explain 3-tier architecture diagrams, system context diagrams, system interaction diagrams, etc.
- Proven experience building enterprise-grade, AI-focused solutions on the cloud (Azure, AWS, GCP) for customers, from Minimum Viable Products (MVPs) leading to production deployments.
- DevOps and MLOps: Strong understanding of DevOps practices and CI/CD tool chains, and familiarity with MLOps (AI & ML lifecycle management) for sustainable enterprise grade deployments.
- Competitive Landscape: Understanding the competitive landscape is valuable, candidates should be aware of key AI platforms beyond Azure, such as AWS and GCP. Knowledge of the AI open-source ecosystem.
Responsibilities
Customer-Centric Approach:
- Understand customers’ overall data estate, business priorities, and IT success measures.
- Innovate with AI solutions that drive business value.
- Facilitate scalable delivery through strong technical programme management utilizing a factory model/approach; driving programme awareness and demand across the regional areas.
- Ensure Solution Excellence: Deliver solutions with high performance, security, scalability, maintainability, repeatability, reusability, and reliability upon deployment. Gather insights from customers and partners.
Business Impact:
- Drive Consumption Growth: Develop opportunities to enhance Customer Success and help customers extract value from their Microsoft investments.
- Unblock Customer Challenges: Leverage subject matter expertise to identify resolutions for customer blockers. Follow best practices and utilize repeatable IP.
- Build repeatable IP and assets that create velocity in deployment and drives customer value from their Unified investment. Continuously look to improve upon these assets utilizing the best of field inputs.
- Architect AI Solutions: Apply technical knowledge to design solutions aligned with business and IT needs. Create Innovate with AI roadmaps, lead POCs and MVPs, and ensure long-term technical viability.
Technical Leadership:
- Advocate for Customers: Share insights and best practices, collaborate with the Engineering team to address key blockers, and influence product improvements, roadmap and feature prioritization.
- Continuous Learning: Stay updated on market trends, collaborate with the AI technical community, and educate customers about the Azure AI platform.
- Accelerate Outcomes: Through engaging with field teams, share expertise, contribute to IP creation, and promote reusability to accelerate customer success, as well as collate feedback on assets to drive improvement and leverage field teams inputs.
Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.
- Industry leading healthcare
- Educational resources
- Discounts on products and services
- Savings and investments
- Maternity and paternity leave
- Generous time away
- Giving programs
- Opportunities to network and connect
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Cloud Solution Architect - Azure AI / Machine Learning, Berkshire employer: TN United Kingdom
Contact Detail:
TN United Kingdom Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Cloud Solution Architect - Azure AI / Machine Learning, Berkshire
✨Tip Number 1
Familiarize yourself with the latest trends in Azure AI and Machine Learning. Follow relevant blogs, attend webinars, and participate in online forums to stay updated on new features and best practices that Microsoft is implementing.
✨Tip Number 2
Network with current employees at Microsoft, especially those in the Customer Experience & Success organization. Use platforms like LinkedIn to connect and engage in conversations about their experiences and insights into the role.
✨Tip Number 3
Prepare for technical discussions by practicing your knowledge of AI concepts and Azure services. Be ready to demonstrate your expertise in areas like Generative AI and MLOps during interviews, as these are crucial for the role.
✨Tip Number 4
Showcase your problem-solving skills by discussing past projects where you successfully implemented AI solutions. Highlight how you overcame challenges and drove customer success, as this aligns with the responsibilities of the position.
We think you need these skills to ace Cloud Solution Architect - Azure AI / Machine Learning, Berkshire
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Azure AI and Machine Learning. Focus on relevant projects, technologies you've worked with, and any specific achievements that demonstrate your expertise in these areas.
Craft a Compelling Cover Letter: In your cover letter, express your passion for AI and how your skills align with the role. Mention specific experiences where you successfully implemented AI solutions or overcame challenges in cloud environments.
Showcase Technical Expertise: Be prepared to discuss your technical knowledge in AI and ML during the application process. Highlight your familiarity with tools like TensorFlow, PyTorch, and your understanding of DevOps practices related to AI deployments.
Demonstrate Customer-Centric Approach: Illustrate your ability to understand customer needs and how you've previously delivered solutions that drive business value. Use examples that showcase your problem-solving skills and your impact on customer success.
How to prepare for a job interview at TN United Kingdom
✨Showcase Your Technical Expertise
Be prepared to discuss your hands-on experience with Azure AI and Machine Learning. Highlight specific projects where you've implemented AI solutions, focusing on the technologies and frameworks you used.
✨Understand Customer Needs
Demonstrate your ability to understand customer business priorities and how your technical solutions can drive value. Prepare examples of how you've successfully addressed customer challenges in the past.
✨Familiarize Yourself with Current Trends
Stay updated on the latest developments in AI and cloud technologies. Be ready to discuss emerging trends and how they can impact customer success, particularly in relation to Azure AI.
✨Prepare for Technical Discussions
Expect to engage in deep technical conversations. Brush up on your knowledge of DevOps practices, MLOps, and enterprise-grade solution architecture to confidently answer any technical questions.