Northwest Ohio · Remote US
Full-Stack Software & AI Engineer
Building full-stack products, production AI implementations, agentic systems, and AI-augmented workflow structures from discovery to implementation and deployment integration. Technical foundations in TypeScript across Angular, Node/NestJS, state management, database structures, and mobile and cloud infrastructure.
A prior career in teaching, writing, organizational leadership, and published authorship shapes how I communicate decisions, handle product development with client-facing solutions, and help teams adopt and implement what gets built. This background allows me to discover, assess, communicate, and build within the full scope of a project's lifecycle.
Applied engineering
Selected client engagements and products spanning discovery, architecture, implementation, continuous integration, deployment, and improvement across varied stacks. Names and proprietary detail are omitted to preserve confidentiality.
AI product engineering
Implemented streaming insights across an Angular, NgRx, and NestJS application. The work covered prompt and tool contracts, incremental UX, state and generation persistence, validation, explicit degraded-mode behavior, and an evaluation harness around the feature.
LLM app development · streaming · persistence · reliability · evals
Application modernization
Advanced a large application across 15 major Angular versions and moved its workspace into Nx. The modernization addressed application code, dependencies, build behavior, and long-term maintainability.
Angular · TypeScript · RxJS · Nx
Mobile and infrastructure
Extended an enterprise web application into mobile delivery with Ionic and Capacitor while rebuilding its AWS infrastructure. The work crossed product, build, deployment, and runtime concerns.
Ionic · Capacitor · Nx · AWS
Multi-tenant business platform
Built a responsive multi-tenant suite spanning time and project tracking, CRM, invoicing, and QuickBooks integration. Established the Nx workspace, NgRx architecture, PostgreSQL data model and migrations, and a full Cypress end-to-end suite.
Angular · NgRx · Nx · PostgreSQL · Cypress · QuickBooks
Legacy replacement
Delivered a working replacement slice from a legacy PHP system into NestJS APIs, NgRx state, Angular interfaces, and Ionic mobile delivery for social-network workflows including messaging and channel groups. The slice proved the path across every application layer.
PHP · NestJS · NgRx · Angular · Ionic · messaging
Business platform modernization
Modernized a complex service-business application toward Angular signals while working across CRM, invoicing, and rule-driven product calculations. Introduced its first end-to-end coverage to protect critical business workflows.
Angular · signals · TypeScript · CRM · invoicing · E2E testing
Release and observability
Carried an Angular and Capacitor application through production release and added Datadog observability so runtime behavior and failures could be examined after deployment.
Angular · Capacitor · Datadog · release engineering
Frontend product delivery
Delivered product work across public-sector and confidential enterprise applications, adapting to existing React and Next.js architectures rather than imposing a preferred stack.
React · Next.js · TypeScript
Engineering lifecycle
I translate goals and constraints into product decisions, explain tradeoffs to stakeholders, establish the application and infrastructure, coordinate implementation and quality, and carry releases into observation and improvement. Communication is the connective skill across the technical lifecycle.
Listen to users and stakeholders, study the existing workflow, and identify the actual constraint.
Turn the vision into requirements, boundaries, priorities, risks, and measurable acceptance.
Make the system, data, state, integration, security, and failure-mode decisions explicit.
Set up repositories, environments, infrastructure, CI, conventions, and delivery paths.
Implement across interfaces, state, APIs, persistence, mobile, cloud, and AI capabilities.
Use tests, review, accessibility, security, performance, and AI evaluation to challenge the work.
Coordinate environments, migrations, CI/CD, releases, rollout, and stakeholder readiness.
Use observability, feedback, incidents, evaluations, and captured knowledge to improve the system.
AI systems & orchestration
I use AI as a cross-cutting engineering layer to extend how I plan, build, review, operate, and learn, not as a substitute for engineering judgment. These systems increase throughput by turning standards, context, evaluation, and repeatable work into infrastructure.
AI Augmented Orchestration System
A cross-tool, versioned substrate for Claude Code, Codex, Cowork, and custom agents, installed across projects through a symlinked global layer and project-owned deployments. It coordinates director/executor roles, layered context, skills, isolated agents, hooks, durable work artifacts, evaluation loops, and workflows for planning, TDD, implementation, parallel review, research, and release.
The architecture applies the 60/30/10 deterministic/rule/model split, progressive context disclosure, and human-owned approval gates so AI extends engineering standards instead of replacing them.
Agent operations
Disposable model sessions operate over durable Postgres state, a message bus, Slack integration, an always-on Railway orchestrator, approval boundaries, and a dashboard. Work is routed by task; parallelism is reserved for decomposable work; agent contexts are isolated; consequential actions pause for human approval; and every run leaves reviewable artifacts.
TypeScript · Node · PostgreSQL/Neon · Slack · Railway
Product system · pre-launch
A web and mobile application with an AI insight engine, persisted generation records, token and cost metadata, fallback behavior, rate limiting, evaluation, and user feedback.
Angular · Ionic/Capacitor · NestJS · NgRx · Postgres · Auth0
Decision system
A structured five-dimension fit workflow with server-canonical scoring and a full-stack web and mobile architecture. The system turns a subjective decision into an explicit, revisable model.
Angular · Ionic · NestJS · Nx · NgRx · Prisma/Postgres
Learning infrastructure
An ongoing technical learning system spanning 13 layers, 100 domains, and more than 500 knowledge pages. It connects a capability map, structured study, project application, and recall practice so gaps become visible and improvement is deliberate.
Direct SDK architecture
A TypeScript prototype built directly on the Anthropic SDK for bounded agents, typed tools, persistence, routing, observability, and evaluation seams. It tests where explicit application code is clearer than adopting LangGraph, Mastra, or another general-purpose orchestration framework.
TypeScript · Anthropic SDK · typed tools · persistence · evaluation
Selected projects
Concrete examples of the capabilities above: an orchestration implementation, an MCP protocol prototype, an end-to-end RAG and LLMOps system, and a focused sample of teaching materials.
Claude Code plugins
A Claude Code implementation of the larger engineering substrate: layered context, skills, isolated agents, deterministic hooks, TDD, eight-lens review with fresh verification contexts, and evidence-first research workflows.
View repositoryMCP server · TypeScript
A bounded MCP server prototype demonstrating protocol design, tools/resources/prompts, credential redaction, symlink containment, read-only trust boundaries, and no arbitrary shell access.
View repositoryLearning lab · Python
An end-to-end RAG and LLMOps research system: structural ingestion, pgvector and full-text hybrid retrieval, reciprocal-rank fusion, local reranking, grounded citations and abstention, LiteLLM model routing, Langfuse traces, and layered evaluations. The Python implementation was AI-assisted; the demonstrated capability is system architecture and validation.
View repositoryTeaching artifacts
Three live browser-native decks created for presentations at religious institutions. They are a deliberately narrow sample of a broader workshop and curriculum practice, included to demonstrate the quality of teaching design and communication rather than the full range of AI training topics.
View live decksBackground & enablement
The earlier career is not separate from the engineering work: it informs discovery, stakeholder communication, authorship, facilitation, mentoring, and the ability to transfer a system to other people.
Moved from no professional software background to an enterprise engineering role in five months through intensive self-directed study and applied projects. The Engineering Map now formalizes that learning practice through structured study, application, recall, and build-defense exercises.
Former secondary computer science and robotics instructor. Designed original project-based curriculum across HTML, CSS, JavaScript, Arduino, and Python.
Created two courses, five modules, twelve lessons, and 24 practical workshop concepts. Delivered AI workshops and provided private, one-to-one assistance for people and teams building practical fluency.
Published author of books, articles, chapters, and academic work, with a prior 13-year career teaching, leading teams, facilitating groups, and communicating across technical backgrounds.
Contact
Full-Stack Software & AI Engineer · Northwest Ohio · Remote US
For software engineering roles and technical conversations:
Email tylerkleeberger@gmail.com