Applied AI Engineer

Microsoft • Redmond, WA

1d • $102,100 - $202,200

About The Position

ACES CØDE is a Microsoft engineering organization focused on reducing operational demand across Microsoft Cloud. Its mission is to turn customer and operational signals into lasting product improvements, intelligent diagnostics, autonomous resolution systems, and AI-powered capabilities. The team aims to prevent operational demand at its source, resolve issues autonomously, and use signals to improve product and support reliability.

The ACES CØDE engineering team is building domain-specific agents and services to shift Azure customer support from reactive, human-dependent workflows toward AI-first systems capable of resolving issues at Azure scale. The Applied AI Engineer will translate product specifications into production-ready, scalable AI services using LLM orchestration, multi-agent coordination, and retrieval-augmented generation (RAG). The role includes shipping production services that directly affect Azure customers and owning AI service components throughout their lifecycle, from design and development through deployment, monitoring, and incident response.

Microsoft describes its mission as empowering every person and organization to achieve more. Employees are expected to bring a growth mindset, innovate, collaborate, and uphold respect, integrity, accountability, and inclusion.

Requirements

• Bachelor's degree in Computer Science or a related technical field and 2+ years of technical engineering experience coding in languages such as C, C++, C#, Java, JavaScript, or Python, or equivalent experience.
• Ability to meet Microsoft, customer, and/or government security screening requirements, including passing the Microsoft Cloud Background Check upon hire or transfer and every two years thereafter.

Nice To Haves

• Master's degree in Computer Science, AI, or a 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, including prompt engineering, RAG, or agent frameworks.
• Familiarity with Azure services such as 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 AI evaluation frameworks, including rubrics, golden datasets, and 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, including RBAC, Managed Identities, and secrets management.
• Experience working in Agile or sprint-based delivery with cross-organization dependencies.
• Strong problem-solving skills and ability to thrive in a fast-paced, collaborative environment.

Responsibilities

• Translate product specifications into AI service architectures, including 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 and token optimization, and RAG pipeline design.
• Build evaluation systems using rubrics, golden datasets, and judge agents to validate agent correctness and safety before production deployment.
• Write production-quality C# and Python using test-driven development, and ensure services meet reliability, performance, and security standards.
• Deploy services using CI/CD pipelines, feature flags, and staged rollouts, with production observability through tracing, logging, and 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 agent development to ensure 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.

Benefits

• Certain roles may be eligible for benefits and other compensation; additional benefits and pay information is available through Microsoft's careers website.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level