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# Software Engineering IC6

- **Company:** Microsoft
- **Location:** Mountain View, CA, United States
- **Experience:** Expert
- **Salary:** $165,600 - $296,400
- **Contract:** Permanent contract
- **Skills:** C (Programming Language), Java (Programming Language), JavaScript (Programming Language), Artificial Intelligence, Microsoft Online Services, C Sharp (Programming Language), C++ (Programming Language), Code Review, Continuous Integration, DevOps, Python (Programming Language), Microsoft Security Essentials, Microsoft Software, OpenAI, Azure Machine Learning, Software Engineering, Large Language Models, Prompt Engineering, Model Validation, Information Technology, Performance Monitor
- **Published:** November 12, 2026
- **Apply:** https://www.careerbuilder.com/job-details/software-engineering-ic6-mountain-view-ca--3cec4bf9-21aa-46f2-bbaf-4fad8ec4de92

## About the Role

Software Engineering, Integrated Circuits (ICs), Microsoft Product Family, Data Science, Software Engineering, Software Design, Technical/Engineering Design, Artificial Intelligence (AI), Machine Tool, Product Lifecycle, Required/Minimum Qualifications (RQs/MQs)

 * Bachelors 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 partnering directly with customers or internal stakeholders to deliver solutions end-to-end.

Additional or Preferred Qualifications (PQs)

 * Masters 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 Bachelors 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.
 * Experience designing, deploying, and operating AI or LLM-based solutions, including prompt engineering, retrieval-augmented approaches, model tuning, evaluation, data quality, performance monitoring, and use of cloud AI platforms
 * Familiarity with deploying and operating AI systems in production environments
 * Understanding of model evaluation, data quality, and performance monitoring
 * Experience using cloud AI platforms (Azure ML, OpenAI, or similar)
 * Enjoy travel and are comfortable with travel up to 25%

#FDE

#MicrosoftFrontierCompany

Software Engineering IC6 - The typical base pay range for this role across the U.S. is USD $165,600 - $296,400 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $220,800 - $331,200 per year.

## Description

* Security and responsible engineering: Design, build, and ship secure software by default; apply Microsoft security and privacy practices, threat modeling, and safe deployment patterns to protect customers and the Microsoft cloud.
 * Lead discovery with customers and stakeholders: Partner with customer engineering teams and domain experts to understand business goals, constraints, and success measures; translate them into clear technical requirements and solution approaches.
 * Deliver end-to-end solutions: Architect and implement cloud and AI solutions-from prototype to production-using modern engineering practices (code reviews, testing, CI/CD, observability) and partnering closely with Microsoft product teams and partners.
 * Move fast with quality: Use iterative delivery to de-risk technical decisions early, improve reliability through automation, and continuously learn and adapt as customer needs evolve.
 * Drive measurable customer impact: Deliver solutions that meet agreed success metrics, support adoption, and enable customer teams through coaching, knowledge transfer, and clear documentation.
 * Build reusable, scalable assets: Create reference implementations, frameworks, and best-practice patterns that can be reused across customers and contribute to the broader Microsoft ecosystem.
 * Lead through ambiguity: Navigate complex, fast-changing problem spaces (especially in AI) and guide teams toward pragmatic decisions that balance value, feasibility, compliance, and risk.
 * Collaborate across disciplines: Work effectively with product, design, data science, security, and operations partners; create an inclusive environment where diverse perspectives improve outcomes.
 * Technical leadership and mentoring: Set technical direction, unblock teams, and mentor engineers through design reviews and hands-on guidance; influence senior stakeholders by communicating tradeoffs and recommendations clearly.
 * Embody our culture and values