Open to full-time Applied AI / Generative AI / AI Platform roles

Applied AI Engineering

Building AI systems that are useful, governed, and engineered to hold up.

I build applied AI systems that connect model intelligence with production engineering: retrieval, agent orchestration, governed execution, APIs, evaluation, backend architecture, and reliability.

Generative AI · LLMs · RAG · Agentic AI · AI Platform & Backend Engineering

Explore selected workGitHub

Engineering focus

AI capability is only one layer of the system.

The portfolio is organized around implementation evidence: model behavior, application logic, backend architecture, governance, reliability and evaluation.

01

Applied AI

LLM applications, retrieval systems, structured outputs, grounded workflows, evaluation, and human oversight.

02

AI Platforms

Orchestration, policy gates, tool integration, workflow state, auditability, model routing, and operational controls.

03

Architecture & Reliability

Service boundaries, data flows, persistence, authorization, workflow reliability, observability, and deployment architecture.

04

Backend Engineering

Python, FastAPI, TypeScript, PostgreSQL-oriented systems, REST APIs, Docker, tests, and production-minded service design.

Selected engineering

Six projects, six distinct signals.

Flagships lead with Applied AI depth. Supporting projects prove product, backend, governance and workflow-systems range.

Flagship · Agentic AI / AI PlatformActive flagship

Agentic AI Platform

Governed agent orchestration and controlled execution

Flagship agentic AI and AI-platform project with public evidence for role routing, approval and risk controls, controlled-execution boundaries, provider abstraction, deterministic evaluation, testing, and CI. Broader platform development extends into multi-agent orchestration, governance, auditability, and MCP integration.

  • Role routing and approval / risk controls
  • Controlled-execution boundaries
  • Provider abstraction and deterministic evaluation
  • Automated testing and GitHub Actions CI
PythonpytestGitHub ActionsEvaluationHuman Approval
View repository
Flagship · Regulated AI / RAGActive flagship

Pharma AI Platform

Grounded and traceable regulated-AI contracts

Regulated-AI engineering showcase with public evidence for retrieval-evidence contracts, citation identity, grounded outputs, structured summaries, traceability, human-review transitions, testing, and CI. Retrieval, document-intelligence, and LLM expansion remain broader platform directions.

  • Retrieval-evidence and citation contracts
  • Grounded-answer and structured-summary contracts
  • Human-review transitions and trace IDs
  • 8 automated tests and GitHub Actions CI
PythonDataclassesEnumpytestGitHub Actions
View repository
Featured · Product EngineeringPortfolio-ready showcase

Job Copilot

Job intelligence and workflow product

A product-engineering project focused on governed job ingestion, normalization, freshness, deduplication, candidate intelligence, and application workflow design.

  • Deterministic ingestion contracts
  • Freshness and deduplication logic
  • Type-safe public showcase
  • Vitest verification and CI-oriented structure
TypeScriptReactNode.jsVitestGitHub Actions
View repository
Supporting · Responsible AI / EvaluationSupporting project

HR AI Content System

Governed enterprise retrieval

Governed enterprise-retrieval project implementing SentenceTransformer embeddings, semantic search, deterministic PII redaction, role-conditioned governance, grounded extractive answers, and evaluation.

  • SentenceTransformer embeddings and NumPy-backed retrieval
  • Deterministic PII / sensitive-term redaction
  • Role-conditioned governance; RBAC-aware retrieval is roadmap
  • 17-test unit/integration suite and GitHub Actions CI
PythonSentence TransformersNumPyscikit-learnGradiopytest
View repository
Supporting · Backend EngineeringSupporting project

Medicine Verification Platform

Typed backend API and service architecture

Backend/API engineering showcase implementing FastAPI, Pydantic contracts, service and repository boundaries, synthetic regulatory-source adapters, structured verification outcomes, health checks, testing, and CI.

  • FastAPI health and verification endpoints
  • Pydantic request / response validation
  • Service, repository, and regulatory-source abstractions
  • 7 automated tests and GitHub Actions CI
PythonFastAPIPydanticpytestGitHub Actions
View repository
Supporting · Reliability / Workflow SystemsSupporting project

Nudge

Workflow contracts and reliability-oriented state management

Systems-engineering showcase implementing scheduled-work contracts, queue eligibility, idempotency requirements, explicit lifecycle states, controlled transitions, delivery outcomes, testing, and CI.

  • Pending → queued → completed / failed lifecycle
  • Queue eligibility and idempotency-key validation
  • Invalid-transition and delivery-order enforcement
  • 8 automated tests and GitHub Actions CI
PythonDataclassesEnumpytestGitHub Actions
View repository

Technical surface

Built across AI, backend, product and systems.

Publicly evidenced across the portfolio

PythonFastAPIPydanticTypeScriptReactSentence TransformersSemantic RetrievalEvaluationHuman-in-the-LoopREST APIspytestVitestGitHub ActionsAI GovernanceReliability Engineering

Broader engineering experience & platform direction

Generative AILLM ApplicationsRAGHybrid RetrievalAgentic AIModel RoutingPostgreSQLSQLAlchemyNext.jsPrismaAuthenticationDockerObservability

Portfolio principle

Evidence over buzzwords.

Public claims should map back to implementation, tests, architecture, evaluation, deployment evidence, or professional experience. Planned capabilities stay labeled as planned until they are verifiable.

Connect

Applied AI, platform engineering, and systems work.

Texas, USA · Open to Remote & Relocation. For opportunities, technical conversations, or project review, use any of the links below.