Senior Applied AI Engineer

The Senior Applied AI Engineer role at Microsoft (ACES CØDE) focuses on designing, building, and operating production agentic AI services that improve AI-first support experiences at Azure scale.

Responsibilities

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

Requirements

• Bachelor's Degree in Computer Science or a related technical field AND 4+ years of technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python, or equivalent experience.
• Ability to meet Microsoft, customer and/or government security screening requirements for this role.
• Microsoft Cloud Background Check: required to pass upon hire/transfer and every two years thereafter.

Preferred Qualifications

• Experience building or integrating with LLM-based systems, including prompt engineering, RAG, or agent frameworks.
• Familiarity with Azure services such as Azure OpenAI, Azure AI Foundry, Azure Functions, Cosmos DB, or comparable 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 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 across product, platform, research, and partner engineering teams on complex co-development initiatives.
• Strong business judgment with experience linking engineering investments to customer and operational outcomes.
• Background in customer support engineering, supportability, diagnostics, or customer-experience platforms is a plus.

Technologies

• C, C++, C#, Java, JavaScript, Python
• LLM orchestration, RAG pipelines, agent workflows
• Azure OpenAI, Azure AI Foundry, Azure Functions, Cosmos DB
• CI/CD, Microsoft Agent Framework, feature management
• Container orchestration, infrastructure as code
• Prompt engineering, rubrics, golden datasets, judge models, simulations
• Offline evaluation, online evaluation
• Azure data sources
• Tracing, logging, metrics, alerting

Location and Compensation

• Location: Redmond, WA (onsite)
• Salary: USD 119,800 - 261,000 per year

Minimum Education

Bachelor's Degree in Computer Science or related technical field.