LJ
Available for new opportunities

Leeon John

AI Engineer/
Agent Systems

I build production-oriented AI systems focused on reliability, evaluation, agent orchestration, and developer tooling.

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Flagship Project

OpenSourcePilot

AI-powered open-source contribution assistant that analyzes GitHub repositories, understands issues, performs semantic code search, generates implementation plans, drafts pull requests, and creates test suites.

opensourcepilot — agent

$ pilot analyze https://github.com/org/repo/issues/42

✓ Repository cloned and indexed

✓ 847 files vectorized in ChromaDB

✓ Issue understood: Add pagination support

→ Searching relevant files…

Found: src/api/routes.py (0.94)

Found: src/models/pagination.py (0.89)

→ Generating implementation plan…

→ Writing test suite…

✓ Pull request drafted (PR #43)

$

Tech Stack

PythonFastAPIChromaDBOpenRouterLangChainGitHub APIDockerVector SearchLLM-as-Judge

Agent Workflow

GitHub Issue

Ingests any GitHub issue URL and parses the problem statement

Repository Analysis

Clones and maps the codebase structure, dependencies, and patterns

Semantic Search

ChromaDB vector search finds the most relevant files and functions

Contribution Planning

Planning agent drafts a step-by-step implementation strategy

Test Generation

Auto-generates test suites covering edge cases and happy paths

Pull Request Drafting

Produces a complete, ready-to-submit PR with description and code changes

Project Ecosystem

Systems I've Built

Click any project to explore its architecture, challenges, and engineering decisions.

Currently Building

What I'm Shipping

Active projects in production, staging, and active development.

Active

OpenSourcePilot

AI-powered open-source contribution assistant that analyzes GitHub repos, understands issues, generates implementation plans, and drafts pull requests autonomously.

Progress75%

Current Focus

  • Semantic search v2
  • Multi-repo analysis
  • PR validation loop
PythonFastAPIChromaDBOpenRouter
In Progress

ResearchPilot MCP

Agent workflows powered by the Model Context Protocol — giving research agents structured access to tools, memory, and external knowledge sources.

Progress45%

Current Focus

  • MCP server implementation
  • Tool registry design
  • Agent integration
PythonMCP ProtocolTypeScriptLLMs
Early Stage

BenchLytics

LLM evaluation and observability platform — benchmark models, track performance over time, and surface regressions before they hit production.

Progress25%

Current Focus

  • Benchmark suite design
  • Judge architecture
  • Metrics schema
PythonFastAPIPostgreSQLStreamlit
Engineering Focus

Areas of Expertise

The domains where I design, build, and ship AI systems.

Agentic AI Systems

Designing multi-agent pipelines with Planner, Executor, Critic, and Retriever roles. Autonomous retry loops, structured outputs, and reliable task decomposition.

LangChainOpenAIFastAPIRedis
OrionAIOpenSourcePilot

MCP Infrastructure

Building Model Context Protocol servers and clients that expose structured tools to AI agents — enabling reliable, composable agentic workflows.

MCP ProtocolTypeScriptPythonTool Registry
ResearchPilot MCP

LLM Evaluation

Systematic evaluation using LLM-as-judge rubrics, benchmark suites, and iterative self-refinement. Scoring consistency, factuality, and reasoning quality.

EvaluateOpenAIRubricsPandas
EvalynxBenchLytics

AI Reliability

Hardening AI pipelines against hallucinations, prompt injection, and silent failures. Structured outputs, validation gates, and critic-loop feedback.

PydanticGuardrailsStructured OutputsLogging
EvalynxOrionAI

Retrieval Systems

Building production-grade RAG pipelines with chunking strategies, embedding models, and retrieval ranking. Hybrid search combining dense and sparse methods.

ChromaDBFAISSLangChainEmbeddings
OpenSourcePilotEduRAG

Developer Tooling

Building ergonomic CLI tools, APIs, and dashboards that make complex AI systems accessible and observable for engineering teams.

FastAPICLITypeScriptStreamlit
OpenSourcePilotCode Insights AI

AI Deployment

Containerizing and deploying AI systems with Docker, managing async workloads with FastAPI, and monitoring inference latency and cost.

DockerFastAPIVercelRailway
OrionAIOpenSourcePilot
System Architectures

Under the Hood

How the systems are actually designed. Hover nodes for detail.

OpenSourcePilot

End-to-end agent pipeline from GitHub issue to pull request

GitHub API

Issue & repo ingestion

Repository Analysis

Codebase understanding

Vector Search

ChromaDB semantic retrieval

Planning Agent

Implementation strategy

Test Generation

Automated test suites

PR Drafting

Ready-to-submit pull request

Technical Stack

Tools & Technologies

The full spectrum of tools I use to design and deploy AI systems.

L

LangChain

Agent orchestration & chains

O

OpenAI API

GPT-4o, embeddings

O

OpenRouter

Multi-model routing

A

Anthropic

Claude models

L

LlamaIndex

Data framework for LLMs

Full Stack

LangChainOpenAI APIOpenRouterAnthropicLlamaIndexPythonFastAPIRedisPostgreSQLTypeScriptMCP ProtocolMCP ServerMCP ClientTool RegistryChromaDBFAISSOpenAI EmbeddingsBM25RerankingLLM-as-JudgeEvaluateRAGASPytestCustom RubricsDockerVercelRailwayGitHub ActionsNext.jsStreamlitPydanticAsync Python
GitHub Activity

Open Source Work

Building in public at @coderleeon

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Get in Touch

Let's Build Something

Open to AI engineering roles, interesting projects, and collaborations on agentic systems, MCP infrastructure, and evaluation platforms.