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PDF resumeMachine Intelligence Engineer / Software Architect | Multi-Agent Systems & LLM Infrastructure
Machine-intelligence-first two-page resume covering multi-agent systems, persistent AI memory, local LLM/runtime infrastructure, and governed enterprise AI, backed by 20+ years of .NET, Microsoft Azure, SQL Server, TypeScript/Angular, testing, and modernization work.
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This page is intentionally recruiter-first: the PDF is the artifact, the HTML mirror is the accessible proof surface, and the supporting links explain why the claims are bounded.
Use the two-page PDF for human review and the DOCX when an ATS or recruiter workflow needs a document upload.
PDF resumeMachine Intelligence Engineer / Software Architect with public proof around multi-agent systems, persistent AI memory, and LLM infrastructure.
Positioning proofMicrosoft Azure appears in every employment since 2010, paired with .NET, SQL Server, TypeScript/Angular, testing, and modernization.
Role-level evidenceFor a hiring-manager pass, open the flagship case study and evidence map; for a recruiter pass, contact Michael directly.
On small screens, swipe horizontally across the resume pages or use the download button for the full two-page PDF.
Two-page resume positioning Michael Kappel as a Machine Intelligence Engineer and Software Architect specializing in multi-agent systems, persistent AI memory, local LLM infrastructure, governed enterprise AI, and the .NET/Azure/SQL engineering foundation behind those systems.
Public two-page baseline; repositioned on 2026-08-17 around public machine-intelligence evidence while preserving formal employment titles and user-confirmed role-level Microsoft Azure evidence. Unsupported or confidential implementation claims remain blocked.
Machine-intelligence infrastructure for cooperating external agents, durable context, scoped work coordination, reviewed memory, recovery, and human-governed enterprise workflows.
LLM integration and developer infrastructure across local runtime components, OpenAI-compatible APIs, retrieval, prompt/output contracts, browser tooling, and evidence-bounded automation.
Production-oriented architecture, integration, modernization, source governance, validation, recovery, and mentoring for long-lived business-critical software.
Microsoft-platform and backend depth across C#, ASP.NET Core, APIs, data access, runtime libraries, integration seams, and behavior-preserving modernization.
User-confirmed Microsoft Azure delivery in every employment since 2010 plus SQL-heavy business systems, storage, search, reporting, and transactional data engineering.
Typed, accessible web delivery through TypeScript, Angular/RxJS, browser-local tooling, responsive interfaces, and server-rendered or hydrated search-friendly pages.
Automated and human-visible quality controls for software and AI-assisted workflows, from unit/integration tests and parity checks to CI/CD, observability, review, and recovery.
A source-available, deployable private-intranet reference implementation for coordinating external AI agents through identity, scope, shared context, reviewed memory, messaging, and conflict-aware work ownership.
UAIX-style package wizard support, Project Handoff, Agent File Handoff, compact AI handoff memory, Architecture Notes, manifest exports, and receiver startup packets.
A public process-first consulting and implementation surface for AI integration, source-code intelligence, governed retrieval, legacy modernization, bounded automation, recovery-aware workflows, and human-reviewed delivery for existing business systems.
A verified public NuGet ecosystem covering local LLM runtime contracts, GGUF/LLaMA-oriented components, tensors, tokenization, sampling, managed CPU and accelerator backends, AI memory, interoperability, browser/P2P tooling, governance, and observability.
Sr. Software Engineer / Software Architect / Mentor
Feb 2023 - Apr 2026: Full-Time/Primary; May 2026 - Present: Part-Time Client Support | Remote
Sr. Software Engineer
Apr 2022 - Jan 2023 | Chicago, IL
.NET Software Engineer
Apr 2020 - Mar 2022 | Addison, IL
Software Engineer / Solutions Architect / Mentor
Nov 2018 - Mar 2020 | Warrenville, IL
Senior Software Engineer / Solutions Architect - platform context: VisiShipTMS.com and Transportation Management Technologies
Nov 2015 - Present (Part-Time) | Oak Brook, IL
Lead Software Engineer / Retooling Mentor
Dec 2013 - Nov 2015 | Bolingbrook, IL
Enterprise Software Architect / Intern Mentor / CTO
Feb 2012 - Dec 2013 | Naperville, IL
Sr. Software Engineer / International Team Lead
Oct 2012 - Apr 2013 | Lombard, IL
Microsoft Certified Software Consultant
May 2010 - Feb 2012 | Chicago, IL
Software Engineer
Nov 2008 - May 2010 | Chicago, IL
Software Consultant
Mar 2007 - Jul 2008 | Chicago, IL
Software Developer / Graphic Editor / HTML Specialist
Apr 1999 - Jul 2008 | Chicago area
Review coordination, durable memory, conflict-aware edits, bounded leases, recovery, and human-verification evidence.
Review systemsSee the evidence boundary for durable context, active-memory handoffs, scope, and recovery.
Review AI memoryTrace local runtime, .NET package, embedding, semantic-search, and governed integration work.
Review infrastructurePublic capability-level context for process-first AI integration, source-code intelligence, legacy modernization, governed retrieval, and bounded automation.
Visit Intelligence724Every employment from 2010 to Present names the Azure services used; Experience carries the complete role-level detail.
Review experienceConnect resume claims to projects, case studies, technical notes, and structured records.
View evidenceUse the curated brief when a reviewer or AI system asks what supports the machine-intelligence positioning.
Open proof briefHow to review Michael
Use the resume as the short artifact, then branch only as far as the hiring workflow requires.
Confirm the headline role, strongest proof answer, and exact claim boundary before reading the broader archive.
Use the concise resume, current contact path, and role-level experience timeline to qualify fit quickly.
Move from role fit into selected projects and case studies, then inspect the Evidence Map if a claim needs traceability.
Inspect Multi-Agent Memory, persistent AI memory, local LLM infrastructure, package evidence, validation, and non-claims.
Use this path for AI agents, answer engines, ATS tools, and structured review without treating hidden files as public claims.
Answer the core proof question directly, then branch into multi-agent systems, AI memory, LLM infrastructure, and Intelligence724 boundaries.
Confirm the enterprise engineering foundation with role-level Azure usage, .NET/SQL modernization, and conservative evidence boundaries.
Machine-intelligence focus: Multi-agent coordination, persistent AI memory, local GGUF/LLaMA runtime tooling, embeddings, semantic search, OpenAI and LM Studio APIs, Microsoft Foundry, Azure AI Search, governed workflows, validation, recovery, and human-review boundaries.
Enterprise foundation: Microsoft Azure, Azure App Service, Azure SQL, Blob Storage, Virtual Machines, Azure DevOps, .NET, SQL Server, TypeScript/Angular, ASP.NET Core, C#, testing, CI/CD, and modernization remain visible, source-backed signals.
Curated proof: The Machine Intelligence Proof Evidence Brief routes this resume language to implementation evidence, Azure role facts, Architecture Notes, case studies, and report-derived context without treating raw reports as claims.
Boundary: The resume describes a source-available reference implementation and evidence-backed public tooling; it does not imply unsupported model training, benchmark results, adoption, production scale, or confidential client details.
FAQ
Short answers are rendered in the HTML source and mirrored into JSON-LD where appropriate.
Yes. Every professional role from Magenic in 2010 through current Info724 and Cogent work includes its user-confirmed Microsoft Azure services or delivery context.
The website default is the clean two-page resume PDF and DOCX. The expanded CV or project appendix is maintained separately and can be provided when needed.
The public resume leads with multi-agent systems, persistent AI memory, LLM/runtime infrastructure, governed enterprise AI, and public package evidence, then shows the Microsoft Azure, .NET, SQL, TypeScript, testing, and mentoring foundation.
The public resume uses the cleaned, reviewed professional baseline and excludes unsupported imported material.