Microsoft
Senior Software Engineer - FDE
$120K–$261K
United States +8 · On-site · Senior · Full-time · Posted Oct 20, 2026
- Location
- United States
Redmond, WA
Mountain View, CA
Houston, TX
Austin, TX
Chicago, IL
New York, NY
Cambridge, MA
Atlanta, GA - Experience
- 4+ years technical engineering experience; preferred alternatives: 6+ years with a Master's Degree, or 8+ years with a Bachelor's Degree, or equivalent experience.
- Education
- Bachelor's Degree in Computer Science or related technical field, or equivalent experience.
- Visa sponsorship
- Microsoft is unable to sponsor a work visa for this role.
About the job
Build and operate secure, scalable production software while working with customer teams to turn business needs into deployed solutions.
What you'll do
- Design, build, test, and operate production-grade software and services; deliver customer solutions end-to-end.
- Partner with customers and internal stakeholders to define requirements and success metrics, then translate needs into technical designs.
- Lead technical workstreams and promote engineering practices such as code reviews, automated testing, CI/CD, observability, and documentation.
What they ask for
- Bachelor's Degree in Computer Science or related technical field and 4+ years of technical engineering experience coding in a listed language, or equivalent experience.
- Coding experience in languages including C, C++, C#, Java, JavaScript, or Python.
Nice to have
- Master's Degree in Computer Science or related technical field and 6+ years of technical engineering experience, or Bachelor's Degree in the field and 8+ years, or equivalent experience.
- Customer or stakeholder partnership delivering solutions end-to-end; experience designing, deploying, and operating AI or LLM-based solutions; willingness to travel up to 25%.
Pay
USD $119,800 - $234,700 per year (base salary); USD $160,200 - $261,000 per year (base salary)
Tools
C, C++, C#, Java, JavaScript, Python
AI focus
Apply AI across the development lifecycle; preferred experience includes designing, deploying, and operating AI or LLM-based solutions, including prompt engineering, retrieval-augmented approaches, model tuning, evaluation, data quality, performance monitoring, and cloud AI platforms.
Model-written summary · the original posting is authoritative