Works intensely across all phases of software delivery — conceptual design, detailed design, implementation, testing, and production deployment — on a large-scale enterprise insurance claims platform. Leads internal architecture discussions, collaborates closely with business analysts to clarify requirements and define technical deliverables, and contributes to the strategic direction of the software. Maintains current knowledge of market trends including AI/ML and cloud-native patterns.
Responsibilities:
Architected and delivered a multi-tier microservices platform for enterprise insurance claims processing, spanning 30+ ASP.NET Core Web APIs organized across distinct Experience, Process, and System service layers to enforce separation of concerns and independent deployability
Built full-stack Blazor WebAssembly applications (MudBlazor, Fluxor/Redux state management, FluentValidation) and React SPAs for claims management portals serving adjusters, TPA users, and management teams
Wrote intermediate to advanced T-SQL queries, stored procedures, and schema designs across multiple MSSQL databases; applied service-oriented architecture patterns throughout the platform
Drove DevOps maturity through Azure DevOps CI/CD pipelines, Docker containerization, and environment-stratified configuration management (Dev UserTest Production)
Conducted regular code reviews to enforce quality standards, identify design issues early, and grow technical capability across the team; contributed to defining and documenting coding conventions adopted platform-wide
Mentored junior and mid-level engineers through pair programming and architectural guidance; developed GitHub Copilot onboarding guides and AI usage standards for developers and business analysts
Qualifications:
Additional Experience (Nice to Have):
Designed and built a custom agentic AI workflow engine enabling configurable, multi-step AI reasoning pipelines — supporting tool execution, memory scoping, verification steps, and structured output — without hardcoded orchestration logic; applied across claims triage, coverage determination, and document analysis
Built and maintained a Retrieval-Augmented Generation (RAG) service backed by Azure AI Search, powering AI-assisted features including compensability and coverage determination workflows, document data extraction, photo analysis, and automated notes summarization using Azure OpenAI