AI Engineer | Infrastructure & Product Builder
Building the future of open-source AI orchestration and local-first LLM infrastructure.
- ๐ Graduate Degree in Data Science with a focus on high-performance AI systems.
- ๐ ๏ธ Core Focus: Shipping production-ready AI products, local-first LLM gateways, and decentralized AI.
- ๐ฆ Active Contributor & Builder with OpenClaw: Dedicated to improving the OpenClaw ecosystem and building tools that make AI more accessible and private.
- ๐ Infrastructure-Minded: Bridging the gap between complex ML models and scalable, secure DevOps practices.
OpenBrain is a local-first, OpenAI-compatible gateway designed to unify fragmented AI provider APIs into a single, secure, and manageable interface.
- Unified API Gateway: Exposes a single
/v1endpoint for any OpenAI-compatible provider (Groq, vLLM, Ollama, xAI). - Virtual Key Management: Create one "virtual app key" for your local applications while managing multiple provider keys behind the scenes.
- Dynamic Routing: Switch the primary backend model on the fly without changing a single line of code in your apps using the
model="default"route. - Local-First & Secure: Includes encrypted key storage, rate limiting, CSRF protection, and a local dashboard for real-time monitoring.
- Observability: Built-in usage logging and Prometheus metrics for tracking performance across different backends.
- Inference: vLLM, Ollama, LM Studio, Groq, OpenAI API
- Tooling: OpenClaw, LangChain, Model Gateways (OpenBrain)
- Frameworks: PyTorch, TensorFlow, Scikit-learn, HuggingFace Transformers
- Languages: Python (FastAPI/Flask), SQL, Java, C++, R
- Database: NoSQL (MongoDB), Vector DBs (Chroma, Pinecone), SQL
- Interfaces: Streamlit, CLI Tools, Local Dashboards
- Platforms: AWS, GCP, Azure
- Deployment: Docker, Kubernetes (Minikube/K8s), Terraform
- CI/CD: GitHub Actions, Jenkins, Automated Model Retraining
- OpenClaw: I am actively building on and improving OpenClaw to enhance its capabilities in decentralized AI execution and interoperability.
- Open-Source: Focused on building "connective tissue" for AIโtools that make it easier for developers to switch models, manage costs, and keep data local.