Responsibilities- Customer-Centric Approach
• Develop a deep understanding of customers' business priorities, application landscape, and AI readiness, linking technology decisions to measurable outcomes.• Design and deliver AI application and Agent-based solutions that create tangible business value.• Drive scalable delivery through structured technical programme leadership, leveraging a factory-based approach to create visibility, demand, and execution consistency across regions.
• Ensure solution excellence by delivering production-grade solution accelerators that meet requirements for performance, security, scalability, reliability, and reusability.
• Capture and synthesise insights from customers and partners to continuously improve delivery patterns and solution quality. - Business Impact
• Drive consumption and value realisation by identifying opportunities to expand customer adoption of AI applications and Agents across their estate.• Unblock complex customer challenges by applying deep technical expertise and leveraging best practices and reference architectures.• Build and scale reusable assets, patterns, and IP that accelerate delivery velocity, reduce time to production, and maximise customer value from AI investments.
• Architect end-to-end AI solutions, translating business requirements into scalable architectures, guiding customers from ideation (POC/MVP) through to enterprise-grade production deployments. - Technical Leadership
• Champion customer needs by providing structured feedback to Engineering, influencing platform capabilities, roadmap direction, and feature prioritisation-particularly across AI apps, agents, and model lifecycle.• Act as a technical thought leader in AI applications and Agentic systems, staying ahead of industry trends and advancing adoption of modern design patterns• Scale impact across the field by sharing expertise, contributing to reusable IP, and driving consistency in AI application and agent delivery approaches.
• Continuously build and elevate technical capability across teams, enabling higher technical intensity and accelerating customer outcomes at scale. - Agentic software engineering
• The candidate should understand how software engineering is changing with AI agents and coding copilots. They should be credible in technical conversations about how AI changes the way applications are designed, built, tested, deployed, and operated.
• Use GitHub Copilot, coding agents, and AI-assisted development workflows to accelerate prototyping, documentation, test creation, and code review.
• Design agentic applications with clear roles, tools, memory, orchestration, guardrails, human-in-the-loop checkpoints, and failure handling.• Apply engineering discipline to AI systems: source control, CI/CD, test automation, model and prompt evaluation, telemetry, rollback, and secure deployment.
• Understand patterns such as tool calling, MCP, RAG, multi-agent workflows, prompt and version management, model evaluation, and AI observability.
QualificationsRequired Qualifications: - Bachelor's Degree in Computer Science, Information Technology, Engineering, Business, Liberal Arts, or related field AND 2+ years experience in cloud/infrastructure technologies, information technology (IT) consulting/support, systems administration, network operations, software development/support, technology solutions, practice development, architecture, and/or consulting
- OR equivalent experience.
Other Requirements:- Microsoft is unable to sponsor a work visa for this role due to the nature of the role's job duties.
- Ability to meet Microsoft, customer and / or government security screening requirements are required for this role. These requirements include, but are not limited to the following specialized security screenings: Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud Background Check upon hire / transfer and every two years thereafter.
Preferred Qualifications:- Bachelor's Degree in Computer Science, Information Technology, Engineering, Business, Liberal Arts, or related field AND 5+ years experience in cloud/infrastructure technologies, information technology (IT) consulting/support, systems administration, network operations, software development/support, technology solutions, practice development, architecture, and/or consulting
- OR Master's Degree in Computer Science, Information Technology, Engineering, Business, Liberal Arts, or related field AND 3+ years experience in cloud/infrastructure technologies, technology solutions, practice development, architecture, and/or consulting
- OR equivalent experience.
- 2+ years experience working in a customer-facing role (e.g., internal and/or external).
- 2+ years experience working on technical projects.
- Technical Certification in Cloud (e.g., Azure, Amazon Web Services, Google, security certifications).
- Application Development & Integration:
- Proficiency in modern programming languages such as Python, C#, JavaScript, or similar, in the context of building AI-powered applications.
- Experience integrating AI solutions with broader Azure services (e.g., Azure Functions, AKS/Kubernetes, API Management, event-driven architectures).
- AI Solution Architecture:
- Proven ability to design and communicate end-to-end AI application architectures, including system context, interaction flows, and multi-tier designs.
- Solid understanding of LLM application patterns, including prompt design, grounding strategies, evaluation techniques, observability, and cost/performance optimisation.
- Familiarity with enterprise considerations such as security, compliance, and scalable deployment of AI solutions.
- DevOps, MLOps & Production Readiness:
- Solid understanding of DevOps practices and CI/CD pipelines, with experience operationalising AI applications in production environments.
- Familiarity with MLOps / LLMOps practices, including model lifecycle management, monitoring, and continuous improvement.
- Responsible AI:
- Understanding of Responsible AI principles, including safety, bias mitigation, governance, and ethical considerations in AI solution design.
- Ecosystem Awareness
- Awareness of the broader AI ecosystem and competitive landscape, including platforms such as AWS and GCP, as well as relevant open-source frameworks and tools.
Cloud Solution Architecture IC3 - The typical base pay range for this role across the U.S. is USD $86,100 - $169,800 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $113,300 - $187,400 per year.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay
Cloud Solution Architecture IC4 - The typical base pay range for this role across the U.S. is USD $106,400 - $203,600 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $137,600 - $222,600 per year.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
