About the job
Customer Success Engineering (CSE) within the Commercial Engineering and AI (CEAI) organization builds and manages critical products and services that Microsoft runs on. We pursue big ideas that power transformational advances for Microsoft and its customers while helping teams work smarter, faster, and more securely every day. We are looking for Software Engineers who are passionate about building good software and continuously learning new technologies. If you’re excited to build, experiment, and shape the future of commercial execution with AI at the core, we invite you to apply.
Responsibilities
Brainstorm and identify solutions for critical business and technical problems, using AI as a thought partner to accelerate ideation, weigh alternatives, and pressure-test trade-offs
Be innovative in identifying solutions to the functional and non-functional requirements
Design, develop, and deploy solutions which help in improving experiences for Microsoft Industry Solutions Delivery (ISD) and Customer Experience & Success (CE&S) businesses. Use AI-assisted and agentic engineering workflows to move from idea to production faster while upholding quality, security, and reliability.
Leverage AI Native Engineering practices and contribute to the Organizational Knowledge and Context for Agents to be more effective. Continuously curate this organizational knowledge so copilots and agents produce higher-quality, better-grounded results for the whole team.
Analyze events and telemetry from multiple sources and resolve issues in small term and identify patterns for long term solutions, and apply AI/ML for anomaly detection and faster root-cause analysis
Partner with peer teams in leveraging and extending the services and experiences for bigger and broader impact
Design, build, and integrate AI-powered capabilities—copilots, agents, and generative AI features—into our products, applying prompt engineering, grounding, and retrieval-augmented generation (RAG) to deliver reliable, high-quality outcomes.
Champion Responsible AI: use systematic evaluations (evals) to measure quality, and ensure solutions are safe, secure, grounded, and trustworthy.
Qualifications
Minimum
Good development experience using Azure resources and services
Good exposure to VSO, Git and modern engineering practices
Well versed with Agile development methodology
Good experience using Microsoft technology stack and/or other languages (.NET framework, ASP.NET, C#, PowerShell, SQL).
Ability to create insights from App Insights and Kusto
Hands-on experience using AI-assisted development tools (such as GitHub Copilot and coding agents) and ‘vibe coding’ to design, write, test, and review code is a important.
Good verbal and written communication skills.
4+ years of relevant work experience
Preferred
Hands-on experience or exposure to React and/or other JavaScript Frameworks would be a plus
Exposure to AI Native Engineering—building with large language models (LLMs), agent frameworks, prompt engineering, and retrieval-augmented generation (RAG) is strongly preferred
Familiarity with the Azure AI platform (such as Azure OpenAI Service and Azure AI Foundry) is a plus
Working knowledge of Responsible AI principles and AI evaluation practices is a plus