20 hours ago
Responsibilities
- Architect and build production agentic AI systems with LLM orchestration, multi-agent workflows, RAG pipelines, tool integrations, memory and state management, and human-in-the-loop experiences.
- Write, review, and maintain production-quality C# and Python code, including reusable components, reference implementations, prototypes, and platform capabilities.
- Own end-to-end technical delivery from requirements and experimentation through implementation, deployment, operation, and continuous improvement.
- Define architecture patterns, API and data contracts, code quality expectations, evaluation practices, deployment strategies, and observability standards.
- Develop evaluation frameworks using rubrics, golden datasets, simulation, judge models, and offline and online evaluation.
- Ensure production services meet standards for correctness, availability, latency, scalability, cost, safety, and reliability, including incident response and root cause analysis.
- Design responsible and secure AI systems with privacy protections, prompt-injection defenses, tool authorization, data boundaries, action controls, auditability, and fail-safe behavior.
- Evaluate models, frameworks, platforms, and architectural approaches using experiments and production telemetry.
- Influence product and platform roadmaps and partner across product, research, platform, and Azure service teams.
- Use operational data to improve automation accuracy, case volume reduction, resolution time, engineering efficiency, and customer satisfaction.
- Lead architecture reviews, resolve technical disagreements, align partner organizations, and mentor engineers across teams.
Requirements
- Bachelor's degree in Computer Science or a related technical field and 6+ years of technical engineering experience with coding in languages including C, C++, C#, Java, JavaScript, or Python, or equivalent experience.
- 8+ years of professional software engineering experience designing, building, and operating production software systems is preferred.
- Strong proficiency in C# and/or Python and experience designing 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 engineering practices including microservices, APIs, containers, CI/CD, infrastructure as code, and observability.
- Ability to influence technical direction and align multiple teams without direct management authority.
- A master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related technical field is preferred.
- Experience implementing agent security patterns such as prompt-injection defense, identity propagation, least-privilege tool access, data-boundary enforcement, approval gates, and auditable actions.
- Ability to move between strategic architecture and detailed implementation while debugging complex interactions across models, prompts, tools, data, and distributed services.
- Business acumen and experience connecting technical investments to measurable customer outcomes.
- Track record of mentoring senior engineers and raising engineering standards without formal people management responsibilities.
- Background in customer support engineering, supportability, diagnostics, or customer experience platforms is a strong plus.
Tech Stack
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.