Principal AI Engineer

Microsoft•Redmond, WA

12d

About The Position

Microsoft is a company where passionate innovators come to collaborate, envision what can be and take their careers further. This is a world of more possibilities, more innovation, more openness, and the sky is the limit thinking in a cloud-enabled world. Microsoft’s Azure Data engineering team is leading the transformation of analytics in the world of data with products like databases, data integration, big data analytics, messaging & real-time analytics, and business intelligence. The products our portfolio include Microsoft Fabric, Azure SQL DB, Azure Cosmos DB, Azure PostgreSQL, Azure Data Factory, Azure Synapse Analytics, Azure Service Bus, Azure Event Grid, and Power BI. Our mission is to build the data platform for the age of AI, powering a new class of data-first applications and driving a data culture. Within Azure Data, the messaging and real-time analytics team provides comprehensive solutions and a robust platform that enables users to ingest high granularity signals (real-time & observability) and complex data, converting those into a competitive advantage in real-time for both end users and modern applications. The Real-Time Intelligence team is hiring a Principal AI Engineer to lead real-time AI that powers agentic workflows on live operational data. You will drive capabilities such as autonomous agents, anomaly detection at scale, and decisioning that closes the loop from detection to action. In this role, you’ll set the technical direction for our agentic systems, LLMOps stack, and evaluations platform, building shared foundations while also shipping customer-facing features that help organizations understand, react to, and automate their real-time data. We do not just value differences or different perspectives. We seek them out and invite them in so we can tap into the collective power of everyone in the company. As a result, our customers are better served.

Requirements

- Bachelor's Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.
Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include, but are not limited to the following specialized security screenings: Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.

Nice To Haves

- Master's Degree in Computer Science or related technical field AND 12+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR Bachelor's Degree in Computer Science or related technical field AND 15+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.
- Demonstrated experience shipping LLM-powered features or agentic systems in production (e.g., copilots, assistants, workflow agents, tool-calling systems).
- Experience with at least one major cloud platform (Azure, AWS, or GCP) and modern infrastructure practices (microservices, containers, orchestration, CI/CD).
- Strong proficiency in Python (and/or another backend language such as C# or Java) and experience building production services or platforms.
- Proven ability to define architectures, make trade-offs, and lead multi-team projects from design through launch.
- Background in evaluation of ML/LLM systems: designing test sets, rubrics, human and auto-rater evaluation pipelines.
- Excellent communication skills and the ability to explain complex trade-offs to both technical and non-technical stakeholders.

Responsibilities

- Design and ship autonomous agents that can reason, plan, and execute multi-step workflows, integrating with MCP tools, APIs, action registry, and internal data sources.
- Build and evolve the evaluations platform (offline evals, golden datasets, LLM-as-judge/auto-raters) and integrate it into CI/CD so every model, prompt, and agent change is tested before and after release.
- Partner cross-functionally with product, design, research, and data science to establish observability and quality guardrails for LLM and agent workloads, including telemetry, tracing, dashboards, and metrics for task success, safety, cost, and latency, and use them to support A/B tests and phased rollouts.
- Provide technical leadership and mentorship, setting standards for design, coding, eval practices, and Responsible AI, while driving multi-team initiatives that raise the bar for reliability and user impact.
Embody our culture and values

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