11 hours ago
Base Salary
$143k - $304k/yr
Responsibilities
- Lead end-to-end development of cloud-native applications, APIs, platform services, and full-stack engineering disciplines.
- Architect and deliver generative AI platforms, copilots, agentic systems, and intelligent applications.
- Design AI-ready data platforms, knowledge systems, scalable AI services, APIs, and orchestration frameworks.
- Drive technical strategy and architecture for Applied AI solutions across engineering, data science, product, and business teams.
- Create reusable AI frameworks, SDKs, and platform services that improve productivity, performance, scalability, governance, and reliability.
- Establish practices for Responsible AI, AI governance, model evaluation, security, compliance, observability, and operational excellence.
- Provide hands-on technical leadership through architecture reviews, code reviews, mentoring, and direct technical contribution.
- Partner with business and technology leaders to identify and deliver transformational AI opportunities.
- Turn emerging AI technologies into scalable platforms, reusable services, and enterprise-wide solutions.
Requirements
- A master’s degree in a relevant field plus 4+ years of applicable experience, or a bachelor’s degree in a relevant field plus 6+ years of applicable experience, or equivalent experience.
- 5+ years of experience working in data-intensive Azure environments and translating business requirements into scalable data and AI solutions.
- Deep expertise with Microsoft Fabric, Azure AI Foundry, Azure Data Platform, Synapse Analytics, and Azure App Service.
- Hands-on experience with Python or modern programming languages such as C#, Java, or Scala.
- Experience designing and implementing generative AI, LLM, RAG, semantic search, vector database, and agentic AI solutions.
- Preferred experience building and deploying copilots, intelligent agents, multi-agent systems, and enterprise AI applications.
- Preferred expertise in AI platform engineering, LLM orchestration, knowledge graphs, prompt engineering, model tuning, and AI evaluation frameworks.
- Preferred experience operating cloud-scale services using software engineering and SRE practices, including reliability, observability, automation, and service excellence.
- Preferred experience with MLOps, LLMOps, AI observability, model governance, and production AI operations.
- Preferred success leading enterprise-scale cloud, data, analytics, and AI transformation initiatives.
- Demonstrated ability to mentor engineers and drive architecture decisions, engineering strategy, and cross-functional execution.
- Ability to meet Microsoft, customer, and government security screening requirements, including the Microsoft Cloud Background Check.
Benefits
- The typical U.S. base pay range is $142,800–$274,800 per year; the San Francisco Bay Area and New York City metropolitan area range is $188,000–$304,200 per year.
- Certain roles may be eligible for benefits and other compensation.
- The position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until filled.
Categories
About Microsoft
Microsoft develops operating systems, productivity software, cloud services, developer tools, and consumer devices for individuals, enterprises, and governments. Its main products include Windows, Microsoft 365, Azure, Visual Studio/GitHub, Xbox, and LinkedIn; revenue comes from software subscriptions and licenses, cloud consumption, hardware sales, and advertising. Founded in 1975 and headquartered in Redmond, Washington, Microsoft is a public company traded on Nasdaq.