Job description

Overview ACES CØDE is a Microsoft engineering organization focused on reducing operational demand across the Microsoft Cloud, including but not limited to the avoidable support cases, repeated troubleshooting, and manual interventions that arise when cloud products, platforms, or processes do not work as intended. Our mission is to engineer this demand out of the Microsoft Cloud by turning customer and operational signals into lasting product improvements, intelligent diagnostics, autonomous resolution systems, and AI-powered capabilities. As cloud services grow in scale and complexity, we are moving beyond simply reacting to problems after they occur. We work to understand why operational demand exists, prevent it at the source where possible, resolve it autonomously when it does occur, and continuously learn from those signals to make our products and support experiences more reliable. We look for teammates who can navigate ambiguity, reason from data and customer signals, work across technical and organizational boundaries, and turn complex problems into durable, measurable outcomes. Within this mission, the ACES CØDE engineering team is building domain-specific agents and services that are transforming Azure customer support from reactive, human-dependent workflows toward AI-first systems capable of resolving customer issues at Azure scale. We are seeking an Applied AI Engineer to help build the next generation of production agentic AI services that resolve customer issues faster, reduce avoidable support demand, and improve the reliability and scalability of AI-first support experiences. 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 our team provide our customers with the world-class cloud services they need to succeed. Microsoft's 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 Key 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 : Bachelor's Degree in Computer Science or related technical field AND 2+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience. Other: Ability to meet Microsoft, customer, and/or government security screening requirements is required for this role. These requirements include, but are not limited to, the following specialized security screening: Microsoft Cloud Background Check. This position is required to pass the Microsoft Cloud Background Check upon hire or transfer and every two years thereafter. Preferred Qualifications • Master's degree in Computer Science, AI, or related field. • 4+ years of software engineering experience in C# and/or Python, with production deployment experience. • Experience building or integrating with LLM-based systems (prompt engineering, RAG, or agent frameworks). • 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. • Strong understanding of data structures, algorithms, and system design fundamentals. • Experience with multi-agent orchestration and agent-to-agent communication protocols. • Experience with evaluation frameworks for AI systems (rubrics, golden datasets, judge agents). • Familiarity with RAG pipelines and vector retrieval systems. • Experience with container orchestration, microservices architecture, and cloud-native deployment patterns. • Experience with security best practices (RBAC, Managed Identities, secrets management). • Experience working in Agile/sprint-based delivery with cross-org dependencies. • Strong problem-solving skills and ability to thrive in a fast-paced, collaborative environment. • #EngOps #EngOpsACES Software Engineering IC3 - The typical base pay range for this role across the U.S. is USD $102,100 - $202,200 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 $133,800 - $219,200 per year. Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: careers.microsoft.com This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled. Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Requirements

Must-haves

Every day, our customers stake their business and reputation on our cloud. You can help our team provide our customers with the world-class cloud services they need to succeed.
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.

Nice-to-haves

Master's degree in Computer Science, AI, or related field.
Experience building or integrating with LLM-based systems (prompt engineering, RAG, or agent frameworks).
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.
Strong understanding of data structures, algorithms, and system design fundamentals.
Experience with multi-agent orchestration and agent-to-agent communication protocols.
Experience with evaluation frameworks for AI systems (rubrics, golden datasets, judge agents).
Familiarity with RAG pipelines and vector retrieval systems.
Experience with container orchestration, microservices architecture, and cloud-native deployment patterns.
Experience with security best practices (RBAC, Managed Identities, secrets management).
Experience working in Agile/sprint-based delivery with cross-org dependencies.
Strong problem-solving skills and ability to thrive in a fast-paced, collaborative environment.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

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