Now

Current Focus

• Building reliable backend and data platforms.
• Learning MLOps fundamentals step by step.
• Improving operational reliability through better system design and delivery practices.

Learning

• Golang for backend services, concurrency patterns, and simpler deployable tooling.
• Databricks-style bronze, silver, and gold data layering for cleaner pipelines.
• MLflow basics for experiment tracking and model lifecycle workflows.
• RAG architecture with LangChain and practical retrieval tuning.
• Vertex AI concepts, semantic caching, and latency/cost trade-off design.

Open To

I am open to working with small teams, freelance clients, and early-stage products that need help turning ideas into stable systems.

• Backend architecture, API design, and system design discussions.
• Data pipelines, ETL workflows, and DeAAS-style support for early AI adoption.
• AI app reliability reviews, especially for fast-built or AI-assisted products that need stronger operational discipline.
• Long-term engineering roles where backend, data, and system modernization are central.