React / TypeScript
Interactive browser applications, typed UI state and reusable interfaces, demonstrated in the workforce and CodeSentinel applications.
ENGINEERING STACK · 2026
This matrix maps the technologies and competencies identified from the target engineering roles to the most natural canonical project. “Implemented” means there is concrete repository evidence; “Demo” means a bounded technical demonstration; “Boundary” means it is deliberately not claimed yet.
Interactive browser applications, typed UI state and reusable interfaces, demonstrated in the workforce and CodeSentinel applications.
Natural fit for a dedicated client against the existing API systems; kept as a bounded frontend demonstration rather than mixed into unrelated applications.
Natural .NET UI companion for the HealthTech/API family and a stronger demonstration of end-to-end C#.
Public healthcare API work with backend services, validation, tests, Docker and CI.
EventForge uses a Node/TypeScript API as an actual service boundary in a polyglot event-driven system.
Typed API boundaries and data tooling are represented in the engineering lab and analytics projects.
EventForge uses separate JVM and Go consumers to demonstrate real service boundaries rather than language-name badges.
Cloud platform engineering, containers, Kubernetes, infrastructure and automated delivery are demonstrated publicly.
EventForge models PostgreSQL, Kafka, Node API and Go consumer in one development-time distributed application model.
A Wolverine-based Kafka consumer demonstrates message-handler routing and transport abstraction alongside the lower-level consumer.
Relational modelling, SQL analysis and PostgreSQL-backed application components are present across the portfolio.
Security is represented through secure boundaries, authentication/authorization concepts, CI security and repository verification.
HealthTech implements ECDSA P-256 signature verification and AES-256-GCM round-trip encryption for synthetic artifacts. The keys are ephemeral or in-memory demo keys, not production key management.
Descriptive device statistics and synthetic-data handling are demonstrated in the HealthTech API. This is not a claim of a trained machine-learning or predictive analytics system.
Vector retrieval belongs naturally in local research tooling. A neural-network claim is kept bounded until a model, training/evaluation and reproducible evidence are part of a public implementation.
Requirements, acceptance criteria, quality gates, root-cause analysis and continuous-improvement documentation are treated as engineering artifacts.
Kept as contextual knowledge rather than a new-build target. Current work uses modern .NET.
The portfolio combines browser clients, APIs, databases, messaging, containers and deployment rather than treating frontend and backend as isolated skills.
No standalone finance or risk implementation is currently promoted with inspectable code and verification. It is excluded from demonstrated engineering capabilities until a specific evidence link is available.