Why me and not another AI consultant?
/ The short version
Most AI consultants know AI. I know systems. The difference is that AI is only 20% of what makes an AI product work in production. The other 80% is architecture, platform engineering, observability, deployment, and organizational design. I do all of it.
Domains I operate across
AI Systems Engineering
Production agent architectures, RAG pipelines, LLM optimization, evaluation frameworks, cost engineering. Not prototypes — systems that survive real users and real data.
Software Architecture & Design
System decomposition, API design, domain modeling, type-driven development, error handling architecture. I think in boundaries, contracts, and failure modes.
Platform Engineering & DevOps
CI/CD, infrastructure as code, container orchestration, observability stacks, deployment strategies. I build the ground your AI system stands on.
Business Process Modeling & DevEx
Organizational process design, developer experience optimization, delivery flow modeling. I understand why teams get stuck — not just the code, but the human systems around it.
Technical Leadership & Mentorship
Architecture decision frameworks, team upskilling, hiring strategy, engineering culture. I transfer capability, not dependency.
Why this combination matters
When your AI agent fails in production, it's rarely an AI problem. It might be a deployment problem, a data pipeline problem, an observability problem, or an organizational problem disguised as a technical one. Most consultants see one layer. I see the full stack — from business model to Kubernetes pod.
Track record
- Staff Engineer at Octa — building production AI systems at scale
- Designed multi-agent systems for fintech, insurance, and enterprise onboarding
- Reduced token costs by 7-12x across multiple client engagements
- Cut onboarding time from 3 months to 1 month with RAG-based platform
- Built document processing pipelines that replaced 3-5 day manual workflows with 10-minute automation
- Shipped PoCs that ran in production for months without intervention
Engineering philosophy
- Systems thinking first. Code is downstream of decisions.
- Augmented Intelligence, not Artificial. Humans steer, machines execute.
- Make illegal states unrepresentable. Encode invariants in types, not runtime checks.
- Engineering changes the real world. If it doesn't ship and survive contact with users, it's not engineering.
- Simplicity is not the absence of complexity. It's the result of hard thinking about what actually matters.
Interested in working together? See consulting formats →