Microsoft
Software Engineering
$102K–$219K
United States · On-site · Full-time · Posted Nov 3, 2026
- Experience
- Required: 2+ years of technical engineering experience coding. Preferred alternatives: Bachelor's Degree and 4+ years; OR Master's Degree and 2+ years; OR equivalent experience.
- Education
- Bachelor's Degree in Computer Science or related technical field; OR equivalent experience.
About the job
Build and operate production software for Microsoft’s datacenter inventory and asset-management workflows, while applying AI and automation to engineering and operational processes.
What you'll do
- Partner with stakeholders to identify operational problems and own solutions from discovery through rollout and impact measurement.
- Design and build inventory services, APIs, workflows, and user experiences; ensure quality, security, reliability, and production readiness.
- Use AI, agents, and automation in engineering and inventory workflows, testing their value through experiments and measurable results.
What they ask for
- Bachelor's Degree in Computer Science or related technical field and 2+ years of technical engineering experience coding; OR equivalent experience.
- Coding experience in languages including C, C++, C#, Java, JavaScript, or Python.
- Ability to meet Microsoft, customer and/or government security screening requirements, including the Microsoft Cloud Background Check.
- Demonstrated ability to communicate clearly, collaborate across teams, and take well-defined features from design through production operation.
Nice to have
- Experience using generative AI models, coding agents, or engineering platforms to build software.
- Experience with cloud platforms, distributed systems, developer tooling, identity and security, observability, CI/CD, testing infrastructure, or safe deployment.
Pay
USD $102,100 - $202,200 per year (base salary); USD $133,800 - $219,200 per year (base salary)
Tools
C, C++, C#, Java, JavaScript, Python
AI focus
Use coding agents, generative AI, automation, and emerging tools in engineering work; identify and validate opportunities to embed AI, agents, and automation in datacenter inventory workflows.
Model-written summary · the original posting is authoritative