Engineering Work

Case studies in production AI, distributed systems, and developer tools. Each one covers the problem, design, trade-offs, testing, and results.

Production AIDistributed systemsDeveloper platformsTesting and validation

Case Studies

Selected case studies

01Public preprint

Applied research

EventFlowSentry

A reproducible fault-injection and metamorphic-testing approach for finding event-time failures in streaming pipelines.

Controlled fault model

Metamorphic oracle

Evidence trail

View case study
02Open-source package

AI infrastructure

kvfleet

A KV-cache-aware routing control plane for self-hosted and hybrid LLM fleets, built around explainable policy, locality, health, and fallback decisions.

Normalize and fingerprint

Filter and rank

Execute and explain

View case study
03Open-source package

Developer tooling

bigocheck

A zero-dependency empirical Big-O checker that turns performance expectations into CLI and pytest assertions.

Generate observations

Fit growth models

Enforce expectations

View case study

Technical Skills

Technology stack

Technologies I use across backend systems, cloud infrastructure, applied AI, developer tools, and data-intensive services.

Cloud Architecture

AWS-based distributed systems designed for reliability, security, and day-to-day operation.

AWSTerraformDockerCI/CDObservability

Backend Systems

Data-intensive services and APIs built for maintainability, observability, and scale.

JavaPythonSpring BootMicroservicesREST

Applied AI

Production generative AI, agent workflows, RAG, and evaluation pipelines with measurable results.

LLMsRAGLangGraphMCPAgentic workflows

Developer Platforms

Tools that find quality, compatibility, and performance problems during development and CI.

ASTMCPPyPIMavenAutomation