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Job Title: Senior Microsoft Software Engineer - Remote
Build and evolve the client's software Bot, the core automation engine behind client's Windows endpoint management platform, while helping shape technical architecture and delivering secure, reliable software in C# and .NET. You will be working on the MicroSoft operating system code. Need to have experience with Power BE, building images, and Intune
Designing, building, testing, and maintaining production software for AidenBot using C# and .NET, with a focus on reliability, security, performance, and maintainability.
Technical design and architecture contributions, including evaluating tradeoffs, defining interfaces and patterns, documenting decisions, and helping the platform evolve without creating unnecessary complexity.
End-to-end delivery of meaningful product capabilities, from refinement and estimation through implementation, code review, automated testing, deployment support, and post-release learning.
Diagnosis and resolution of complex defects and production issues across application code, services, integrations, data flows, and Windows endpoint environments.
Engineering quality through clear, testable code; thoughtful reviews; appropriate automated test coverage; observability; secure development practices; and disciplined source control.
Technical collaboration and mentorship that raises the effectiveness of the engineering team, including sharing context, reviewing designs, pairing on difficult problems, and helping other engineers make sound implementation decisions.
Practical use of AI-assisted engineering and agentic workflows to improve speed and leverage while protecting code quality, security, governance, and release reliability.
Minimum of 8-10+ years of professional software development experience, including substantial hands-on experience building and supporting production applications in C# and .NET.
Strong understanding of software architecture, object-oriented design, APIs, asynchronous processing, data access, integration patterns, and maintainable application design.
Demonstrated ability to take complex features from ambiguous requirements through technical design, implementation, testing, release, and production support.
Experience diagnosing difficult software problems using logs, metrics, traces, debuggers, profilers, and systematic root-cause analysis.
A strong quality mindset, including experience with unit, integration, and automated testing; code review; source control; CI/CD; and reliable release practices.
Working knowledge of relational databases and SQL, including data modeling, query performance, and application-level data access.
Strong written and verbal communication skills, including the ability to explain technical decisions, risks, and tradeoffs to both engineering and non-engineering stakeholders.
Experience working in Agile / Scrum teams and with Azure DevOps, GitHub, or similar planning, source control, build, and deployment systems.
Comfort operating in a smaller, high-accountability growth company where senior engineers balance architecture, hands-on delivery, collaboration, and production ownership.
Experience with BIOS, partitioning, Windows Registry, drive partitioning, Windows PE, and other system-level architectures.
Experience building enterprise SaaS, endpoint management, Windows-based systems, cybersecurity-related products, IT operations software, or automation platforms.
Experience with Windows internals, PowerShell, Microsoft cloud technologies, endpoint administration, or software that executes work across distributed devices.
Experience with cloud services, distributed systems, messaging, REST APIs, authentication and authorization, third-party integrations, or high-volume job orchestration.
Experience using AI-assisted development tools, agentic workflows, or AI-enabled testing in a disciplined production engineering environment.
Developing the client's end point software platform including the Bot capabilities ship predictably and meet clear standards for correctness, security, performance, supportability, and rollback readiness.
The AidenBot codebase becomes easier to understand, test, extend, troubleshoot, and operate as the product and customer base grow.
Architectural decisions are pragmatic, well communicated, and aligned with both near-term delivery needs and the platform's long-term direction.
Complex defects and production issues are resolved methodically, with root causes addressed and lessons translated into better code, tests, telemetry, and engineering practices.
Engineering teammates benefit from thoughtful design collaboration, constructive code review, clear documentation, and practical technical mentorship.
AI is used thoughtfully as a force multiplier for engineering speed and quality without weakening security, maintainability, or accountability.
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