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About Microsoft
Microsoft Corporation is a global technology leader producing software, hardware, and cloud services including Windows, Office 365, Azure cloud platform, Xbox gaming, and Surface devices. Industry: Software & Cloud Computing
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As a Principal Applied AI Engineer, you will architect and build production agentic AI systems, including LLM orchestration, multi-agent workflows, RAG pipelines, and tool integrations. You will perform hands-on engineering by writing and maintaining high-quality C# and Python code to create reusable platform capabilities and reference implementations. Your role involves translating complex customer support scenarios into technical requirements while establishing architecture patterns, API contracts, and evaluation frameworks using rubrics and golden datasets. You will ensure production reliability regarding latency, cost, and safety while implementing security measures like prompt-injection defenses. The work focuses on solving problems within the customer support domain to improve automation accuracy and resolution times. Required skills include expertise in distributed systems, cloud-native practices, and experience with Azure, microservices, containers, CI/CD, and infrastructure as code.
Architect and build production agentic AI systems including LLM orchestration, RAG pipelines, and multi-agent workflows.
Write and maintain production-quality C# and Python code for core components and reusable platform capabilities.
Translate ambiguous customer requirements into technical specifications and manage the full lifecycle from architecture to deployment.
Establish engineering standards for API contracts, data schemas, evaluation practices, and observability for AI services.
Design and implement evaluation frameworks using golden datasets and judge models to define quality thresholds for autonomous operation.
Ensure production reliability by managing latency, cost, safety, and defending against prompt injections or unauthorized actions.
Make high-level technical decisions regarding model selection, framework adoption, and architectural trade-offs based on telemetry.
Mentor engineers and provide technical leadership to align multiple teams around shared designs and engineering standards.
What we're looking for
Bachelor's Degree in Computer Science or related technical field.
Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related technical field (preferred).
6+ years of technical engineering experience with coding in languages including C, C++, C#, Java, JavaScript, or Python.
8+ years of professional software engineering experience designing, building, and operating production software systems.
Strong proficiency in C# and/or Python to design and implement production-quality services and distributed systems.
Experience with applied AI systems including LLM-based applications, prompt engineering, RAG architectures, agent frameworks, or machine learning services.
Experience with cloud platforms (preferably Azure) and cloud-native practices like microservices, APIs, containers, CI/CD, and infrastructure as code.
Background in customer support engineering, supportability, diagnostics, or customer experience platforms (preferred).
Generative AI
LLMs
Agentic AI
RAG
Python
Java
LangChain
AutoGen
Semantic Kernel
Google Vertex AI
OpenShift
Docker
Kubernetes
Microservices
CI/CD
Natural Language Processing
Computer Vision
Deep Learning