Core Technologies
- LLM Orchestration
- RAG Architecture
- Agentic Workflows
- Next.js
- Go
- PostgreSQL
- TypeScript
- Docker
- Redis
- Python
ENGINEERING PORTFOLIO
Designing multi-agent workflows and high-fidelity systems through AI-native engineering. Deep technical expertise that translates into business velocity and product stability.
ENGINEERING STACK & ACTIVITY
Philosophy
Building on robust engineering foundations while orchestrating AI-native workflows. Problem decomposition, agent supervision, and predictable outputs — complexity reserved for where it creates distinct business value.
Activity
Activity (12 wks)78+ PRs Merged
WHAT I’M BUILDING TOWARD
Currently deepening expertise in AI-native engineering patterns. Building real systems, not just prototypes.
Agentic Observability
Exploring monitoring patterns for multi-agent systems — hallucination detection, logic drift, token efficiency. Building evaluation pipelines to ensure reliable AI execution.
Prompt-to-Productivity
Studying the bridge between business requirements and AI-generated codebases. Focused on output quality, latency optimization, and reproducible results.
RAG Architecture
Building retrieval-augmented generation systems with hybrid search. Learning reranking strategies and citation enforcement for production-grade accuracy.