Senior Software Engineer, EngThrive Insights - CoreAI

Join the team defining what AI-first software engineering looks like at Microsoft. EngThrive Insights builds data products that help tens of thousands of Microsoft engineers to work more productively with AI.  We collect thousands of engineering signals daily from across the entire SDLC. We then partner with all levels of engineering – from executives to ICs – to translate the data into tools and programs that maximize AI-fueled productivity.   

 In this role, you’ll build and operate the data services that reveal how Microsoft engineers can improve productivity—and help reshape how the company ships software faster and with higher quality. Along the way, you’ll deepen your expertise in data engineering and dimensional modeling, agentic AI and MCP server development, privacy-by-design metric APIs, and frameworks such as DORA and SPACE, while fronter AI tools to create the next generation of developer insights at Microsoft.

• Partners with software development teams to understand how they evaluate and improve productivity. Uses this insight to design new metrics and measurement approaches for EngThrive Insights. 

• Builds extensible, reliable, and maintainable artifacts (data pipelines, schemas, dashboards, etc.) using AI-first tools and engineering practices. Assesses delivery readiness, minimizes defects, and flags blockers early with clear timeline impacts and mitigation options. 

• Identifies gaps in our technology stack, then helps close them with practical solutions. Evaluates and responsibly reuses internal or open-source code when appropriate, while building awareness of tools beyond the immediate domain. 

• Uses AI tools across the software development lifecycle in a disciplined manner. Reviews every AI-generated change, applies appropriate validation and engineering processes, and remains accountable for the final result. 

• Translates user satisfaction into measurable feedback loops and secure, privacy-aware metrics. Incorporates quantitative signals such as usage and performance, along with qualitative needs such as accessibility and globalization. 

Required Qualifications: 

• Bachelor's Degree in Computer Science or related technical field AND 86+ 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:
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• Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.  

Preferred Qualifications: 

• Master's Degree in Computer Science or related technical field AND 6+ 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 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.
• Experience with dimensional modeling and analytics engineering (e.g., star schemas, medallion architecture, semantic layers).
• Experience with analytical query languages like SQL, KQL (Kusto Query Language) and Azure Data Explorer, or similar analytical query languages.
• Experience developing applications on Spark-based big data platform technologies such as Databricks.
• Experience building REST APIs or MCP servers with web application frameworks.
• Experience building or integrating with LLM-powered tools, AI agents, or MCP (Model Context Protocol) servers.
• Experience with DevOps, CI/CD pipelines, infrastructure-as-code, and production monitoring/observability.
• Quantitative aptitude and ability to reason about metric definitions, data quality, and statistical validity.
• Familiarity with developer productivity metrics and frameworks (e.g., DORA, SPACE, or similar).
• Experience collaborating with data & applied scientists
• Demonstrated effective use of AI coding assistants in daily development workflow