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# Software Engineering - Commercial Engineering & AI...

- **Company:** Microsoft
- **Location:** Redmond, WA, United States
- **Experience:** Experienced
- **Salary:** $85,400.0 - $168,100.0
- **Contract:** Permanent contract
- **Skills:** C (Programming Language), Java (Programming Language), JavaScript (Programming Language), Artificial Intelligence, C Sharp (Programming Language), C++ (Programming Language), Software Debugging, DevOps, Python (Programming Language), Software Engineering, Data Streaming, Reliability of Systems, Build Management, Information Technology
- **Published:** August 7, 2026
- **Apply:** https://www.juju.com/job/00000000glybhb

## About the Role

+ Bachelor's Degree in Computer Science, or related technical discipline with proven experience coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience., + Master's Degree in Computer Science or related technical field with proven experience 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 2+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.

## Description

As a Software Engineer, you will design and build AI-native systems that go beyond supporting workflows-they intelligently transform them. You will work across data, systems, and agentic workflows to enable faster insights, smarter decisions, and higher productivity across the global sales ecosystem.

Responsibilities

 + Understand end-to-end business processes, workflows, and data flows across the Microsoft sales ecosystem, and identify opportunities to simplify, automate, and agentify those experiences.

 + Rapidly prototype and deliver POCs and iterate on solutions using an experimentation-driven engineering approach.

 + Design, build, and ship scalable, production-quality features and intelligent services using modern engineering practices.

 + Collaborate across teams to integrate systems, data, and signals into cohesive AI-powered workflows.

 + Debug, troubleshoot, and improve system reliability and performance using telemetry and diagnostics.

 + Build secure, compliant, and responsible AI solutions ready for production scale.

 + Contribute to a culture of continuous learning, experimentation, and engineering excellence.


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