Alex Chernysh · Staff AI Engineer & Integration Architect
I build agent systems, retrieval layers, and internal AI platforms that stay understandable under real constraints: solid retrieval, clear checks, strong observability, and careful integration work.
Best fit: teams where the model is no longer the whole story and the real engineering work has already started.
Audit
A bounded audit flow that points to likely failure clusters, missing controls, and the first moves worth making.
Walkthroughs
Compact, sanitized walkthroughs for grounded QA, query transformation, approval-heavy agents, and release loops.
Grounded legal QA with a real abstain path
This is the kind of surface that looks fine in a demo and becomes expensive the moment somebody trusts it.
Query transformation for a sparse-doc RAG stack
Query transformation helps when the symptom is real. Otherwise it just adds latency and self-respect leaves the room.
Where I'm useful
I usually get pulled in when the product already exists, trust has become an operational issue, and the next step needs architecture instead of another demo.
Architecture review
For teams with a live or near-live AI system that needs clearer seams, safer defaults, and less accidental chaos.
Grounding and eval audit
For RAG or agent stacks that sound plausible in demos and start slipping the moment real decisions depend on them.
Embedded build shaping
For product and engineering teams that need a senior engineer to shape the workflow, system boundaries, and path to production.
Delivery brief
A bounded planning surface for scope, evals, instrumentation, and rollout order before the initiative turns into a vague AI bucket.
Writing
Writing on retrieval, evals, observability, and integration work once the demo is no longer the main problem.
A short note from Israel on what repeated alarms do to attention, engineering judgment, and team habits — and which working practices make interruption easier to absorb.
A practical blueprint for legal QA, shaped in part by work around the Agentic RAG Legal Challenge: document identity, hybrid retrieval, structured answers, page-level grounding, telemetry, and evals.
A practical guide to LLM product safety: prompt injection, excessive agency, unsafe outputs, evals, and sober boundaries.
Assistant
Useful for questions about architecture, retrieval, production rollout, and where I can help most.
Contact
Available for focused architecture roles, targeted audits, and embedded help during a build phase.
Most useful when there is a live system, a trust problem, or an integration mess that is already slowing decisions down.