What you will own:

·       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.

Required Qualifications:

·       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.

Preferred Background

·       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.

What Success Looks Like

·       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.