12 hours ago
Redmond, WA, USAStaff+
Base Salary
$143k - $304k/yr
Responsibilities
- Architect, build, deploy, and operate production-grade agentic AI solutions, diagnostic experiences, orchestration workflows, and supporting platforms.
- Set technical direction through architecture, engineering strategy, design principles, and reusable enterprise-scale patterns.
- Develop critical production components, conduct design and code reviews, establish testing standards, and resolve complex technical issues.
- Integrate AI solutions with support systems, APIs, knowledge sources, telemetry, enterprise data, access controls, and data-handling processes.
- Advance planning, context and state management, tool use, multi-agent coordination, retrieval, grounding, observability, and failure recovery.
- Build technical, unit, integration, regression, and end-to-end evaluation and testing capabilities for prompts, models, tools, workflows, and integrations.
- Evaluate accuracy, groundedness, task completion, robustness, latency, cost, safety, and failure modes at deployment milestones.
- Deploy and operate services in Microsoft cloud environments while meeting security, privacy, compliance, Responsible AI, reliability, and scalability requirements.
- Define success metrics and telemetry, create monitoring and incident-response mechanisms, and drive continuous improvement for production AI systems.
- Influence cross-organizational priorities and technical tradeoffs, mentor engineers, raise engineering quality, and maintain architecture and operational documentation.
Requirements
- Bachelor's degree in Computer Science or a related technical field and 6+ years of technical engineering experience with coding, or equivalent experience.
- Coding experience in C, C++, C#, Java, JavaScript, or Python, with the ability to contribute directly to production code.
- Preferred qualifications include a master's degree with 8+ years of experience, a bachelor's degree with 12+ years of experience, or equivalent experience.
- Hands-on experience building applied AI systems involving generative AI, large language models, or autonomous agents.
- Experience designing, building, deploying, and operating highly available, secure, and scalable cloud services and distributed systems.
- Experience with APIs, data platforms, observability, testing, production operations, enterprise integrations, security boundaries, identity, data governance, and compliance controls.
- Experience with Azure AI Foundry, Copilot Studio, Power Platform, Azure services, or comparable enterprise AI and cloud platforms.
- Expertise in agent platforms, multi-agent orchestration, retrieval-augmented generation, knowledge systems, AI evaluation, prompt engineering, model selection, or ML infrastructure.
- Experience developing generative AI evaluation frameworks and quality gates covering groundedness, safety, robustness, and task success.
- Strong communication skills for explaining complex technical decisions to engineering, product, business, and executive audiences.
- Ability to meet Microsoft, customer, and government security screening requirements, including the Microsoft Cloud Background Check.
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.