Work

Selected architecture, platform, and delivery engagements with documented outcomes, explicit maturity notes, and conservative evidence framing.

CLOUD ARCHITECTURE · PLATFORM OPERATIONS

Platform Control Tower

Multi-cloud operations and governance control surface.

Showcase build

Evidence-anchored case study with sanitized architecture and workflow visuals.

WALKTHROUGH AVAILABLE

Live environment available on request. Public case study documents the architecture and outcomes.

Request a walkthrough →

Maturity note: Showcase build with production-ready foundation framing. Evidence in release workflows, smoke scripts, and dual-cloud deployment automation supports the maturity position while keeping client-sensitive details private.

Evidence anchors

Control Tower case-study evidence available Open

Challenge: Pipeline visibility, governance signals, and triage workflows were fragmented across tools and manual runbooks.

Approach: Unified FastAPI and aggregation UI workflows with deterministic triage paths and release guardrails.

Role: Sole author across architecture, API implementation, aggregation UI, release automation, and documentation.

Architecture: FastAPI backend + Flask aggregation UI + Snowflake data access + dual-cloud deployment automation.

Key components

FastAPI operational and governance endpoints
Flask aggregation UI over Azure and AWS API sources
Smoke gates, deployment fingerprint checks, scheduled regression

PythonFastAPIFlaskSnowflakeGitHub ActionsAzureAWS

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AI INTEGRATION · PLATFORM-INTEGRATED CONTROLS

Governed AI Platform

Cross-cloud governed RAG reference implementation.

Working PoC

Sanitized excerpt evidence shows represented governed RAG and deterministic DQ flow.

WALKTHROUGH AVAILABLE

Live environment available on request. Public case study documents the architecture and outcomes.

Request a walkthrough →

Maturity note: Working PoC with internal tooling concept framing. Core governed workflow behavior is implemented and demonstrable, while production-performance claims remain intentionally conservative.

Evidence anchors

Governed AI case-study evidence available Open

Challenge: AI retrieval workflows often lack deterministic governance checkpoints and auditable control trails.

Approach: Separated AI enrichment from decision authority via deterministic DQ/policy gates and Snowflake audit persistence.

Role: Sole author across architecture, backend implementation, governance logic, cross-cloud CI/CD, and documentation.

Architecture: FastAPI routers for RAG and DQ flows, Snowflake-backed audit path, and OIDC CI/CD to Azure and AWS targets.

Key components

Citation-grounded RAG query endpoints
Deterministic DQ and policy verdict logic
Audit write-back and authenticated route contracts

PythonFastAPISnowflakeRAGGitHub ActionsAzureAWS

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INTERNAL TOOLING · DELIVERY FOUNDATION

gitpushandpray.ai

Portfolio platform with CI and post-deploy smoke discipline.

Internal tooling concept

Public content surface with repeatable quality gates and conservative claim boundaries.

Maturity note: This site is a production-ready content surface for portfolio evidence, but its primary purpose is proof presentation rather than product runtime claims.

Evidence anchors

Portfolio CI quality-gate evidence placeholder Source: .github/workflows/ci.yml

Challenge: Proof and case-study content needed a single, maintainable public-safe surface for buyers and hiring teams.

Approach: Structured content-driven Next.js build with repeatable quality gates and route-level smoke checks.

Role: Sole owner: UX structure, front-end implementation, content architecture, and release workflow.

Architecture: Next.js App Router + typed content modules + CI quality gates + post-deploy smoke checks.

Key components

Reusable project and case-study rendering model
Lint, typecheck, unit, build, and smoke in CI
Scripted deploy and post-deploy route checks

Next.jsReactTypeScriptTailwindPlaywrightGitHub Actions

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