Senior Software Engineer

We are seeking a Senior Software Engineer to support, enhance, and modernize a Microsoft-based technology stack that serves multiple business teams and customers. This role requires a hands-on engineer who can work directly with stakeholders, understand business processes, translate needs into practical technical solutions, troubleshoot complex issues across both modern and legacy systems, and thoughtfully apply AI tools to improve development, analysis, documentation, and operational support, including a practical understanding of how modern AI/LLM-based solutions are structured and integrated into applications.

The ideal candidate is comfortable balancing new development with day-to-day production support, root-cause analysis, system improvements, clear communication with business partners, and a proven track record leveraging AI toolsets to improve software delivery, analysis, documentation, and operational efficiency.

Communication skills are critical to this position, and this person must be able to establish rapport and work through issues with business users when identifying solutions to business problems.

Core Development Responsibilities:

• Design, develop, maintain, and support enterprise applications using modern .NET (.NET 9 and beyond)
• Work directly with business users, customers, and stakeholders to understand requirements, clarify needs, and recommend practical solutions
• Perform business analysis by documenting processes, identifying gaps, translating business requirements into technical specifications, and validating solutions with end users
• Jump into existing and legacy .NET applications to troubleshoot production issues, analyze unfamiliar code, support integrations, and improve stability and maintainability
• Debug complex application, data, integration, and configuration issues across legacy systems, APIs, SQL Server databases, scheduled jobs, and operational workflows
• Work extensively with Microsoft SQL Server, including writing and optimizing SQL queries, views, stored procedures, and data fixes
• Support and enhance existing database schemas, data integrations, reporting needs, and operational data flows
• Build and maintain APIs and backend services that integrate internal and external systems
• Develop, deploy, and support applications using Microsoft Azure development-related services, including Azure App Service and related cloud application services
• Use AI-assisted development tools to accelerate research, code analysis, debugging, documentation, test planning, and solution design while maintaining sound engineering judgment
• Work with AI/LLM APIs and services (e.g., Azure OpenAI or similar) to prototype and support lightweight AI-enabled features, integrations, or workflows
• Understand and contribute to AI solution patterns such as prompt design, retrieval-augmented generation (RAG), and data grounding approaches, as applied to real business use cases
• Evaluate practical AI use cases that can improve internal workflows, automate repetitive tasks, enhance knowledge retrieval, or support business users more effectively
• Identify opportunities to modernize, refactor, and improve current solutions without disrupting business operations
• Participate in technical discussions and help guide design and architectural decisions

• Communicate clearly with engineers, business partners, customers, and stakeholders throughout discovery, development, testing, deployment, and support

  
  

Customer-Facing and Business Analysis Responsibilities:

• Engage directly with internal customers and business stakeholders to understand operational needs, pain points, priorities, and success criteria
• Lead or support requirements-gathering conversations, working sessions, demos, and follow-ups with business users
• Translate business problems into clear user stories, acceptance criteria, technical tasks, and implementation plans
• Analyze current-state workflows, legacy system behavior, data dependencies, and integration points to determine practical solution options
• Help users validate fixes and enhancements through testing, walkthroughs, and clear communication of expected behavior
• Provide production support by investigating reported issues, reproducing problems, reviewing logs and data, and explaining findings in business-friendly terms
• Document system behavior, support procedures, known issues, and business rules to improve team knowledge and long-term maintainability
• Apply AI-assisted tools and techniques to improve requirements analysis, summarize complex information, draft documentation, explore legacy code behavior, and identify opportunities for automation while keeping the primary focus on solving business and customer problems

Ideal Candidate Traits:

• Customer-focused and comfortable working directly with business users and stakeholders
• Strong communicator who can explain technical issues clearly to both technical and non-technical audiences
• Strong analytical thinker who can ask good questions, uncover root causes, and connect business needs to technical solutions
• Comfortable debugging unfamiliar legacy systems, tracing data flows, reading existing code, and learning how older applications work
• Curious and pragmatic about AI, with a working understanding of how AI/LLM-powered systems function (prompts, APIs, grounding, data flows) and the ability to identify where they can improve productivity, analysis, support, or solution quality without overcomplicating the architecture
• Willing to challenge assumptions, call out risks, and propose practical alternatives
• Strong sense of ownership and a proactive, can-do attitude
• Able to balance production support, business priorities, technical debt, and new development
• Strong independent worker who is ready to jump in and start contributing on a small engineering team

• Experience with modern Javascript UI frameworks (React, Angular, Vue) and ASP.Net.

  
  

Preferred:

• Hands-on experience with AI-assisted development tools, prompt engineering, LLM-based workflows, RAG concepts, or practical AI pilots that support software delivery or business operations
• Experience using AI tools to analyze legacy code, summarize technical documentation, accelerate troubleshooting, generate test scenarios, or improve developer productivity
• Exposure to AI-enabled knowledge retrieval, document search, semantic search, embeddings, vector databases, or chatbot-style solutions for internal business users
• Ability to evaluate where AI can responsibly improve business processes, support workflows, data analysis, documentation, or operational efficiency
• Familiarity with integrating AI capabilities into applications, automation workflows, APIs, or internal tools while considering accuracy, security, usability, and maintainability
• Experience working with AI/LLM APIs (e.g., Azure OpenAI, OpenAI, or similar) to prototype or integrate AI capabilities into applications, automation workflows, or internal tools