Overview

ACES CØDE is a Microsoft engineering organization focused on reducing operational demand across the Microsoft Cloud — 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 intelligent services that are transforming Azure customer support and product quality, moving from reactive, human-only workflows toward AI-first systems that resolve customer issues and product repairs at Azure scale.
We are seeking a Senior Applied AI Engineer to design, build, and operate production agentic AI services that power AI-first support at Azure scale. The ideal candidate brings Azure product knowledge and customer-support experience to engineering decisions—recognizing recurring customer issues, investigating root causes, and determining whether diagnostic capabilities, clearer guidance, or AI agents will deliver the greatest customer benefit. Working across product, support, and engineering teams, you will help prioritize what to build next, translate customer and business problems into scalable technical solutions, and deliver direct, measurable impact for Azure customers. You will write production-quality code, own significant service components, lead technical execution within projects, and help other engineers adopt sound software and applied AI engineering practices.
Every day, our customers stake their businesses and reputations on our cloud. You can help Azure EngOps provide 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

'• Analyze data signals and uncover patterns: analyze support-case trends, customer issue patterns, and authorized technical signals at scale to uncover recurring failure patterns and gaps in Azure diagnostics and documentation.
• Design and build production AI services: Develop scalable agentic AI solutions for Azure diagnostics and documentation using LLM orchestration, RAG pipelines, agent workflows, tool integrations, memory and state management, and human-in-the-loop experiences,
• Lead through hands-on engineering: Write, review, test, and maintain production-quality C# and Python code. Build reusable components, reference implementations, and engineering patterns that accelerate team delivery.
• Own end-to-end technical delivery: Translate customer support scenarios and product requirements into technical designs, then take solutions through implementation, testing, deployment, monitoring, and continuous improvement.
• Build evaluation-driven AI systems: Develop evaluation frameworks using rubrics, golden datasets, simulations, judge models, and offline and online evaluation. Use measurable quality thresholds to guide agents from experimentation toward production operation.
• Engineer for production quality: Ensure services meet requirements for correctness, reliability, availability, latency, scalability, maintainability, cost, and safety.
• Implement secure and responsible AI patterns: Apply privacy protections, prompt-injection defenses, least-privilege tool access, identity and authorization controls, data boundaries, approval gates, auditability, and fail-safe behavior.
• Integrate with Azure services and data sources: Ground agent responses and actions in trusted, current signals by integrating with Azure data sources, APIs, and cloud-native services.
• Operate services in production: Implement CI/CD, automated testing, feature flags, staged rollouts, tracing, logging, metrics, and alerting. Diagnose production issues, participate in incident response, and drive corrective improvements.
• Make evidence-based technical decisions: Evaluate models, frameworks, prompts, retrieval approaches, and architectural options using experiments and production telemetry. Balance quality with reliability, latency, cost, maintainability, and operational complexity.
• Drive measurable customer impact: Instrument solutions and use data to improve automation quality, case-volume reduction, resolution time, engineering efficiency, and customer satisfaction.
• Provide technical leadership within projects: Lead design reviews, resolve technical challenges, coordinate implementation across contributors, and align partner teams around shared interfaces and delivery goals.
• Mentor and raise engineering capability: Support other engineers through code reviews, technical guidance, reusable documentation, and practical coaching in applied AI and production software engineering.
• Collaborate across organizational boundaries: Partner with product managers, researchers, platform engineers, Azure service teams, and support-domain experts to deliver durable solutions and shape future platform capabilities.

Qualifications

Required Qualifications:

Bachelor's Degree in Computer Science or related technical field AND 4+ 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 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

• 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

• Experience with Azure AI Foundry, Azure OpenAI, Microsoft Agent Framework, or comparable enterprise AI platforms.

• Experience designing AI evaluation systems using rubrics, golden datasets, judge models, simulation, adversarial testing, and offline or online evaluation.

• Experience with RAG systems, including indexing, retrieval, ranking, grounding, citation, knowledge freshness, and access control.

• Experience implementing agent-security patterns such as prompt-injection defense, identity propagation, least-privilege tool access, data-boundary enforcement, approval gates, and auditable actions.

• Experience building reliable distributed services with strong standards for scalability, resiliency, performance, observability, and cost efficiency.

• Experience with infrastructure as code, container orchestration, feature management, and staged production deployment.

• Demonstrated ability to lead technical execution, influence design decisions, and mentor engineers without formal people-management authority.

• Experience collaborating with product, platform, research, and partner engineering teams on complex co-development initiatives.

• Strong business judgment and experience connecting engineering investments to customer and operational outcomes.

• Background in customer support engineering, supportability, diagnostics, or customer-experience platforms is a plus.

#EngOps #EngOpsACES

Software Engineering IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 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 $160,200 - $261,000 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.

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.

Senior Applied AI Engineer

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