Agentic AI that works
in production

Projects where software meets intelligence — ML models, data pipelines, LLM applications, automation, or traditional backend/full-stack work. I focus on systems that need to work reliably in production under real constraints.

Yes. I often work embedded with engineering teams—pairing on architecture, reviewing PRs, and unblocking technical decisions. I can also work independently and deliver complete features.

Yes, NDAs are available on request. I handle sensitive projects across industries and understand confidentiality requirements.

Session notes documenting what we covered, decisions made, and an action plan for next steps. For implementation sessions, you get working code and any relevant documentation.

Both. I can advise on architecture and review existing systems, or I can implement complete features from design through deployment. The 50-hour block is ideal for end-to-end delivery.

Python for ML and backends (FastAPI, scikit-learn, PyTorch), AWS for infrastructure, and modern AI tooling. I also work with Next.js/React, PostgreSQL, Redis, and various data tools depending on the project.

We define scope upfront and document acceptance criteria. For hourly work, changes are straightforward—we adjust as needed. For blocks, we maintain a backlog and reprioritize together during weekly syncs.

I'll tell you directly and recommend next steps or refer you to someone better suited. The discovery call exists to ensure we're aligned before any commitment.