
Principal Applied AI Engineering Manager
Required skills
- AI Engineering Manager
- Applied AI
- AI services
- LLM orchestration
- multi-agent workflows
- RAG pipelines
- evaluation systems
- C#
- Python
- TDD
Nice to have
- multi-agent orchestration systems
- agentic AI services
- AI evaluation frameworks
- rubrics
- golden datasets
- judge agents
Role summary
Seeking an AI-curious Engineering Leader to build and lead an Applied AI Engineering pod within Microsoft's Azure EngOps team. This role involves hiring, coaching, and developing a team of AI Engineers, driving the end-to-end lifecycle of production AI agents (including LLM orchestration, multi-agent workflows, RAG, and evaluation systems), and setting technical direction and standards. Responsibilities include ensuring production health, reliability, and responsible AI practices, as well as influencing product roadmaps and demonstrating business impact through KPIs. The ideal candidate has a strong background in applied AI engineering, people management, and a passion for customer success.
Are you a customer-obsessed, AI-curious engineering leader who thrives in an inclusive, collaborative global team? The Azure Engineering Operations (EngOps) team's mission is to transform Microsoft Cloud customers into fans. Through our deep engineering engagements with customers and teams across Microsoft, we analyze and amplify customer needs and drive the vision to improve Cloud quality, security, and reliability. Our culture of growth mindset and empowerment are central to who we are and how we work.
Responsibilities
• Build and lead the AI engineering pod — Hire, coach, and develop a team of Applied AI Engineers; foster an inclusive, high-trust culture where engineers ship production AI services with ownership and velocity.• Own engineering execution for agentic AI services — Drive the end-to-end lifecycle of production AI agents from spec to deployment, including LLM orchestration, multi-agent workflows, RAG pipelines, and evaluation systems.• Set technical direction and engineering standards — Define architecture patterns, code quality bar, evaluation frameworks, deployment practices, and observability standards for the AI engineering pod. Ensure production-quality C# and Python with TDD, CI/CD, staged rollouts, and full observability.• Own production health and reliability — Ensure deployed AI agents meet quality, performance, and safety standards. Drive incident response, root cause analysis, and continuous improvement for agent systems in production.• Build and maintain evaluation systems — Establish evaluation frameworks including rubrics, golden datasets, and judge agents to validate agent correctness and safety before and after production deployment. Ensure agents graduate through shadow mode to autonomous operation with eval gates at each stage.• Influence product and platform roadmaps — Partner with product, platform engineering, and Azure service teams to shape the agentic AI platform direction. Translate customer support patterns and demand signals into engineering priorities.• Drive measurable business impact — Own KPIs including case volume reduction, automation accuracy, resolution time improvement, and customer satisfaction impact. Use data-driven insights to set OKRs and demonstrate engineering ROI.• Ensure responsible AI and compliance — Partner with AI Governance to embed responsible AI practices, PII protection, action boundaries, and audit trails into all agent systems architecturally.• Develop engineering talent — Mentor engineers on applied AI engineering craft, including agentic system design, evaluation-driven development, and the judgment to know where agents should and should not act autonomously. Build career growth paths across AI engineering competencies.
Qualifications
Basic Qualifications
- Bachelor's Degree AND 6+ years experience in low-code application development, engineering product/technical program management, data analysis, or product development OR equivalent experience?
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.
Sample Microsoft interview questions
- 1
Design a system to log messages in order
system designmedium - 2
Design a timer system
system designmedium - 3
Design a key-value store
system designmedium - 4
Design an LLM-based Q&A System
system designmedium - 5
Design a system that delivers firmware updates to devices
system designmedium
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