SaaS Platforms / AI Systems / Cloud Delivery

Platform Stack

The technologies I use to build useful software that can be shipped, tested, and operated.

Frontend

React, TypeScript, Vite, design systems, dashboards, admin tools, and polished product surfaces.

Backend

Go, Python FastAPI, TypeScript APIs, service contracts, event-driven components, and workflow orchestration.

Cloud

Docker, Kubernetes, Kustomize, Terraform, AWS, Azure integrations, and repeatable delivery paths.

AI + Data

LLM tooling, NLP, MCP, MongoDB, PostgreSQL, Redis, NATS, analytics layers, and evaluation workflows.

Capability Map

Searchable stack view
Frontend

React product interfaces

Dashboards, analytics pages, admin workflows, and customer-facing SaaS screens built with React, TypeScript, and Vite.

React TypeScript Vite UI systems
Frontend

Shared product packages

Reusable interface patterns, typed client packages, shared components, and workspace structures that keep multiple surfaces consistent.

pnpm Workspace tooling Typed clients Components
Backend

Go platform services

Service-oriented backends, domain APIs, event consumers, operators, and typed service contracts with Go, Gin, gRPC, and ConnectRPC.

Go Gin gRPC ConnectRPC
Backend

Python FastAPI services

AI-facing APIs, tool services, evaluation endpoints, data processing, and integration services where Python unlocks faster model work.

Python FastAPI pytest Docker
Backend

TypeScript APIs

Public APIs, BFF layers, integration services, reporting endpoints, and product-facing service layers built with TypeScript.

Node.js TypeScript REST Vitest
AI + Data

AI application tooling

LLM-powered features, NLP pipelines, prompt tools, MCP clients and servers, evaluation flows, and agent-style prototypes.

LLM NLP MCP Evaluation
AI + Data

Application data and events

Document data, relational SaaS records, cache-backed reads, async events, and durable workflows using MongoDB, PostgreSQL, Redis, NATS, and Temporal.

MongoDB PostgreSQL Redis NATS Temporal
AI + Data

Analytics and reporting

Operational reporting, analytics dashboards, metric layers, usage telemetry, and data services that make product behaviour visible.

Cube.js Reporting Telemetry Redshift
Cloud

Containerized delivery

Dockerized services, local dependency stacks, repeatable development environments, and deployment-ready application boundaries.

Docker Compose Containers Local dev
Cloud

Kubernetes operations

Environment overlays, service manifests, controller-runtime operators, and platform automation for cloud-native systems.

Kubernetes Kustomize Operators Overlays
Cloud

Cloud infrastructure

AWS-first infrastructure with Terraform, cloud SDKs, serverless components, managed data services, and Azure integration points.

AWS Terraform Azure Cloud SDKs
Quality

Testing and release confidence

Focused quality checks across unit tests, service tests, browser journeys, AI service validation, and integration-level smoke testing.

Vitest Playwright Jest pytest

No matching technologies found.

Reference SaaS Architecture

Product surface

React, TypeScript, Vite, shared UI packages, API clients, and browser tests for critical workflows.

Service layer

Go for core domain services, TypeScript for BFF and product APIs, and Python FastAPI for AI and data services.

Data and workflows

PostgreSQL for core SaaS records, MongoDB for flexible domain data, Redis for cache, NATS for events, and Temporal for durable workflows.

Delivery path

Docker images, Kubernetes workloads, Kustomize overlays, Terraform-managed cloud resources, and focused automated checks.

How this translates

I can move from product idea to working system: define the user flow, build the frontend, design the service boundaries, connect AI and data workflows, containerize the pieces, and shape a deployment path that can grow beyond a demo.