Are you a customer-obsessed, AI-curious problem-solver who thrives in an inclusive, collaborative global team? The Azure Engineering Operations (EngOps) teams mission is to transform Microsoft Cloud customers into fans. Through our deep engineering engagements with customers and teams across Microsoft, we analyze and amplify customer needs and drive the vision to improve Cloud quality, security, and reliability. Our culture of growth mindset and empowerment are central to who we are and how we work.
Our ACES engineering team is at the heart of delivering scalable, intelligent, AI-powered solutions that transform the Azure customer support experience. We are seeking an Applied AI II Engineer to join the team and help build the next generation of agentic AI services that resolve customer issues faster, reduce support volume, and power AI-first support at Azure scale. You will take product specifications and turn them into production-ready, scalable AI services — working with LLM orchestration, multi-agent coordination, and RAG-based systems. You will ship production services that directly impact Azure customers.
Every day, our customers stake their business and reputation on our cloud. You can help Azure EngOps provide our customers with the world-class cloud services they need to succeed.
Microsofts mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.
Responsibilities
• Translate product specifications into AI service architectures — decompose business intent into agent workflows, data source integrations, and scalable
service designs.
• Build agentic AI workflows using Azure AI Foundry Agent Service and Microsoft Agent Framework, including multi-agent coordination, tool integrations,
and agent lifecycle management.
• Develop and iterate on LLM-based solutions including prompt engineering, model selection, cost/token optimization, and RAG pipeline design.
• Build evaluation systems including rubrics, golden datasets, and judge agents to validate agent correctness and safety before production deployment.
• Write production-quality C# and Python with test-driven development, ensuring services meet reliability, performance, and security standards.
• Deploy services using CI/CD pipelines, feature flags, and staged rollouts with full production observability (tracing, logging, metrics).
• Implement secure service patterns including RBAC, Managed Identities, and secrets management.
• Integrate agents with Azure data sources and cloud-native services to ground agent responses in real-time signals.
• Apply Responsible AI practices across all agent development, ensuring outputs are safe, fair, and compliant.
• Execute reliably within sprint and co-development commitments across ACES and partner engineering teams.
• Own the end-to-end lifecycle of AI service components, including design, development, testing, deployment, monitoring, and incident response.
Qualifications
Required qualifications
Additional or preferred qualifications
• Familiarity with Azure services (Azure OpenAI, Azure AI Foundry, Azure Functions, Cosmos DB, or similar cloud-native technologies).
• Experience with CI/CD pipelines, automated testing, and production observability.
• Understanding of data structures, algorithms, and system design fundamentals.