Practical AI engineering for teams shipping production software.
Strategy, architecture, and hands-on implementation of LLM-backed systems — without the hype. We work with engineering teams who need AI features that survive contact with real users.
Engagements scoped to your stage and constraints.
AI Strategy
Roadmaps that connect business outcomes to model capabilities, data realities, and shipping constraints. Build vs. buy decisions you can defend.
Implementation
End-to-end build of agents, RAG pipelines, and LLM-backed product features. From prototype to production with evals, observability, and graceful failure modes.
Architecture Review
Audits of existing AI systems for cost, latency, reliability, and quality. Concrete remediation plans, prioritized by risk and ROI.
Team Enablement
Workshops, pairing sessions, and review cadences that upskill your engineers on modern AI tooling — so the capability stays in-house.
A short, honest path from problem to production.
Discover
Goals, constraints, data, and existing stack. What success looks like, and how we will measure it.
Design
A minimal, evaluable architecture. Clear interfaces, explicit tradeoffs, and a path from prototype to production.
Deliver
Ship, instrument, document, hand off. No black boxes — your team owns the system afterward.
- Evals before opinions.
- Smallest model that works.
- Production constraints from day one.
- Hand-off, not lock-in.
Senior engineering judgment, applied to AI.
Yarmolenko Consulting is an independent practice led by Vladimir Yarmolenko. We help engineering organizations move from AI ambition to AI in production — working alongside your team, not around them.
The work spans strategy, architecture, and code. Most engagements last weeks, not quarters, and end with a system your team can extend on their own.
- Based
- Remote
- Engagements
- Weeks, not quarters
- Stack
- Vendor-agnostic
- Hand-off
- Always
Have a problem worth solving? Let's talk.
Send a short note about what you're building and where you're stuck. You'll hear back within two business days.