Software Engineer focused on high-performance backend systems and autonomous AI pipelines.
Building production-first systems with sharp resource allocation, strict reliability, and a product-first mindset.
I approach software through a systems lens: resource-aware design, disciplined execution, and resilient infrastructure.
- The Physics of Computing: Prioritizing low-level resource management, system-level architecture, and technical rigor over heavy abstraction layers.
- Core Directives: Architecture > Syntax • Consistency > Motivation • Discipline > Excitement
- Distributed Infrastructure: Multi-tenant architectures, decoupled consumer models, and asynchronous task workers using Redis and AWS SQS.
- Data Integrity: Designing secure API layers with granular RBAC, JWT authentication, and relational/vector storage handling.
- Local AI Infrastructure: Autonomous pipeline orchestration using Ollama, n8n, and Stable Diffusion optimized for hardware inference limits.
- Semantic Vector Retrieval: High-speed similarity pipelines utilizing CodeBERT embeddings paired with FAISS vector indexes.
- Deterministic Inference: Signal processing loops featuring energy-based gating and uncertainty quantification.
- Environments & Tools: Native Linux development (WSL), shell scripting (Bash), and application containerization via Docker.
- Cloud & CI/CD: Deployed architectures across AWS (SQS, SES, S3) and Azure, automated via GitHub Actions pipelines.
