ASSURANTCURRENT
Forward Deployed Engineer
Sep 2026 — PresentBringing engineering, product, and applied AI experience together to address business needs.
ENGINEERING · PRODUCT · APPLIED AI
Logan Pappas.
Forward Deployed Engineer
I build software, lead product delivery, and apply AI to practical problems. My background spans enterprise platforms at Assurant, systems engineering at Abbott, and hands-on mobile and backend development.
AssurantEngineering & product
AbbottSystems engineering
TechLinkSoftware & test automation
Montana StateB.S. Computer Science · 2020
01 / PROFESSIONAL EXPERIENCE
From software engineering
to product ownership and AI.
ASSURANTNashville, TN
Technical Product Owner
Oct 2024 — 2026Owned roadmaps and delivery for enterprise commerce and warehouse applications, connecting client needs with engineering execution.
Role highlights
- Led product ownership for Linc, a B2B used-device marketplace, from discovery through launch and international expansion.
- Managed prioritization and backlogs across multiple applications; coordinated stakeholders, sprint planning, and releases.
- Mentored another Technical Product Owner and helped maintain consistency across product work.
- Led delivery of a cloud-based predictive analytics tool supporting operational decisions.
ASSURANTNashville, TN
Full Stack Software Engineer
Aug 2022 — Oct 2024Developed mobile applications and backend services for global warehouse operations.
Role highlights
- Led development of a Flutter carton receiving and scanning application used across Assurant’s global distribution centers.
- Designed and maintained RESTful APIs with .NET and Python, plus MySQL and MongoDB data models.
- Integrated CI/CD practices and Cypress testing to support reliable releases.
- Contributed early product and roadmap decisions before moving into formal product ownership.
ABBOTTRemote
Systems Engineer
Oct 2020 — Aug 2022Supported the delivery and validation of heart failure system software used by hospital teams.
Role highlights
- Designed and implemented test suites with DOORS and ClearQuest.
- Served as a technical liaison across teams working within quality and compliance requirements.
- Resolved software and end-to-end failures to support international releases.
TECHLINK / TSEALBozeman, MT
Software Engineering Intern
Sep 2019 — Oct 2020Worked on front-end development, automated testing, and API validation for enterprise software.
Role highlights
- Built C# testing frameworks to validate software releases and data integrity.
- Tested website behavior and backend APIs using Postman and browser automation tools.
- Worked with Selenium, React, Gherkin, and SpecFlow.
02 / SELECTED WORK
Projects & professional contributions.
Personal apps for travel, budgeting, and meetings,
alongside work delivered in enterprise teams.
Questra.
Turning travel inspiration into a plan.
A mobile travel app that connects destination discovery, saved places, and personalized itineraries. Its AI pipeline extracts and scores location information from social content, then brings that context into trip planning.
- Identify places from captions, geotags, and images.
- Save destinations and organize travel ideas.
- Build day-by-day plans around interests and budget.
Interactive simulation with sample content. No sign-up, production access, or live AI calls. The current demo reflects the React Native / Expo implementation; the project also has an earlier Flutter build.
Loading Questra demo…
BudgetApp.
Personal budgeting, the way I want to see it.
I built this app for my own budgeting. It uses SimpleFIN Bridge to pull financial data from bank and card accounts, then organizes spending, budgets, and goals into views that fit how I like to manage my money.
- Read-only account and transaction sync through SimpleFIN.
- Custom views for spending, budgets, goals, and cash flow.
- AI-assisted categorization and agent workflows.
- A custom MCP server for asking an AI assistant about budget data.
How it’s put together
- Data & backend
- A Node / TypeScript API imports, normalizes, and categorizes transactions. PostgreSQL stores the app’s financial data, budgets, and goals.
- Personal interface
- An Expo mobile app presents monthly and annual budgets, spending trends, and progress toward goals in a format designed for my own use.
- AI & MCP
- AI tools assist with categorization and budget questions. The MCP server exposes structured tools for working with transactions, accounts, budgets, and goals from an assistant.
Transcriber.
From conversation to searchable context.
A macOS menu bar recorder and companion web app I built to capture meetings, find what was discussed, and turn conversations into useful follow-ups. It records microphone and system audio separately, transcribes locally with whisper.cpp, and merges both tracks into a speaker-labeled transcript.
- Capture both sides of a meeting with a live transcript view.
- Search past transcripts and generate AI summaries.
- Ask questions about one meeting or across meeting history.
- Invoke AI mid-meeting with “Jarvis” voice requests.
- Review automatically proposed action items before filing them in Jira.
How it’s put together
- Native capture & local transcription
- The Swift recorder captures microphone and system audio in chunks. whisper.cpp processes the tracks locally; timestamps bring them together into a readable dialogue.
- Search & AI context
- A React interface and Node.js server organize recordings and transcripts. AI features use transcript context for summaries and questions, including answers that reference source meetings.
- Voice-triggered AI during meetings
- The recorder watches new transcript chunks from both audio tracks for “Jarvis,” tolerating small recognition errors. It carries short requests across chunk boundaries and sends the spoken ask with recent meeting context to Claude. The assistant can search earlier transcripts and summaries when the request refers to past discussions; responses appear in the Jarvis activity feed.
- Jira actions & reviewed follow-ups
- With an Atlassian connection, spoken requests can create issues or update descriptions and add comments to referenced issues. Without that connection, the assistant returns feedback and a draft. Separately, automatic action extraction produces proposals for review before filing.
INSIDE TRANSCRIBERACTUAL APP SCREENS
Captured from the actual web interface using sample meetings and sample AI output. Select a screen to enlarge.
Global warehouse
receiving application
Led development of a Flutter application for carton receiving and scanning, deployed across global distribution centers. The work combined mobile engineering, backend services, and a close understanding of warehouse users.
AI-assisted product
& engineering workflows
Designed reusable Claude skills and Jira workflows for product teams. Used Cursor and custom MCP servers to support consistent API and UI development patterns across engineering work.
03 / APPLIED AI & TECHNICAL SKILLS
Applied AI in products & team workflows.
Building features, improving team workflows,
and connecting models to applications.
AI product development
Translate customer needs and emerging AI capabilities into scoped features. Apply that product perspective to enterprise platforms and Questra’s travel-planning experience.
Agent skills & workflows
Use Claude Code, Codex, and Cursor in engineering workflows. Build reusable agent skills and custom MCP integrations, with Paperclip and OpenClaw among the tools I work with for agent coordination.
AI in applications
Connect AI to real product workflows: location extraction and itinerary planning in Questra, local speech recognition with whisper.cpp, and context-aware meeting assistance in Transcriber.
Languages & frameworks
Dart / Flutter · C# / .NET · Python · TypeScript · React · React Native / Expo · Swift · HTML / CSS
AI development tools
Claude Code & Cowork · Codex · Cursor · ChatGPT · OpenAI API · whisper.cpp
Agents & integrations
Paperclip · OpenClaw · Custom MCP servers · Agent skill design · Prompt engineering · AI-assisted Jira workflows
Cloud & deployment
Vercel · Railway · Azure · Docker · Kubernetes · CI/CD
Data & APIs
PostgreSQL · MySQL · MongoDB · Firebase · Node.js · REST / gRPC APIs · SimpleFIN integrations
Product & quality
Product roadmaps · Agile delivery · Stakeholder management · Jira · Cypress · Selenium · Postman · DOORS · ClearQuest
04 / BACKGROUND
Education & early work.
I studied Computer Science at Montana State University and have worked across testing, systems engineering, application development, and product ownership. Today, I bring those perspectives to forward deployed engineering and applied AI.
Montana State University
B.S. Computer Science
November 2020 · Bozeman, Montana- Collaborated with the department head on a course for an international class in Germany.
- Represented the School of Computing on a visit to technology companies in California.
Early work & college projects
Bluetooth-controlled RC car
Built a Swift app to control a team-designed RC car over Bluetooth Low Energy, working with an electrical engineering teammate.
Watch the project ↗Sports & esports community analysis
Used Python and statistics to compare language in sports and esports subreddit comments. An early project combining data collection, analysis, and a written research presentation.
View the project ↗