Temirlan Dzhoroevbuilds AI that ships.
I own the agent orchestration layer in production — multi-tenant tool-calling agents with checkpointed state and memory across 40+ tenants and ~30K requests a day, the hybrid RAG underneath them, and the eval and moderation layers that decide what ships. Six production systems below, all shipped at Redbrick, where the creation platform I scaled reached 10M+ sign-ups.
- 12 years in Korea
- Fluent Korean
- Korean workplace experience
- No visa sponsorship required
Selected
work
Six systems running in production — hybrid RAG with reranking, agent orchestration, streaming codegen, and a platform that reached ten million users. Open any card for the full case study.
Enterprise Agent Platform
Hybrid parsing, hybrid retrieval, cross-encoder reranking — and an agent per tenant on top.
Companion Chat Runtime
A real-time AI companion that remembers, reacts in its own voice, and moves the scene.
Prompt to Playable
Type an idea, watch a playable game build itself — in the browser, mid-stream.
PDF to Lesson
A textbook PDF becomes an interactive lesson — generated multimodally, moderated for the room it runs in.
Model Gateway
The serving layer under both products — routing, moderation, caching, and back-pressure.
3D Studio
A browser 3D game studio that reached 10M users — block scripting, authoritative multiplayer, in-editor AI.
A bit
about me.
One person, three disciplines, and an obsessive standard for craft.
Research, engineering, and product held in a single head — so ideas ship as fast as they’re proven.
I take AI from prototype to production — the messy middle where demos meet real users, latency, cost, and evals. Three years of it at Redbrick: the agent orchestration layer for 40+ tenants, retrieval that actually recalls, and the eval and moderation stack that decides what ships. No hand-waving: measurable systems that hold up.
Before that, a real-time 3D engine behind 54M+ game plays and two years of HCI research — ten publications, six patents. I care about models that are correct, fast, and honest about their limits. The best AI feels less like magic and more like a tool you can actually trust.
Twelve years in Korea, fluent Korean, and a Korean workplace behind me. I work in either language, and I don’t need visa sponsorship.
Agents & Multi-Agent Systems
LangGraph runtimes, tool registries, checkpointed state and per-agent memory, human-in-the-loop escalation, and control flow you can reproduce.
RAG & Retrieval
Hybrid dense + lexical search, structure-aware ingestion, reranking, and ACL inside the query.
LLM Infrastructure
Gateways, key pools, fallback chains, semantic caching, and streaming that survives real load.
Evals & Moderation
LangSmith regression sets, multi-category classifiers with severity triage and escalation, PII redaction, and the observability to prove any of it.
Where the
work happened
Three years of production AI at Redbrick, on top of an embedded systems and HCI research background.
AI Engineer — Redbrick, Seoul
Own the agent orchestration layer in production — 40+ tenants, ~30K requests/day. LangGraph tool-calling agents with checkpointed state and per-agent memory, coordinating up to 8 dependent tool calls per request; checkpoint recovery raised multi-step task success 82% → 96%. Hybrid RAG over 15K+ documents cut hallucination 18% → 4%, and the moderation and evaluation stack I built gates every prompt or model change. The natural-language-to-playable-3D-game pipeline anchored a $1.2M government R&D grant.
3D Frontend Engineer — Redbrick, Seoul
Scaled a browser-based 3D game engine (Three.js, WebGL, TypeScript) behind a creation platform with 10M+ sign-ups and 54M+ game plays; games I shipped on it passed 1M+ combined plays. Led a 50K-line migration from Webpack to Vite with a rebuilt render pipeline and a replaced physics engine — build times −60%, bundles −35%, hot reload 8s to under 1s. Refactored the engine into modular packages to unblock 3 teams in parallel, and redesigned onboarding from session-replay analysis — 7-day activation +25%, Day-30 retention +15%.
Embedded Systems & HCI Researcher — DECS Lab, UNIST, Ulsan
Real-time IoT firmware in C for ARM Cortex-M MCUs driving 50+ networked sensor devices at sub-millisecond latency, powering the data pipeline behind six published studies.
Education
M.S. in Design, Human–Computer Interaction — UNIST
GPA 4.0 / 4.3 · Lotte Scholarship. Thesis: human perception of social robot face and colour expression using computational emotion models.
B.S. in Computer Science & Industrial Design — UNIST
Global UNISTAR Silver Scholarship.
Research
Six conference papers, four journal articles, and six co-filed patents from the DECS Lab years — first author at IEEE RO-MAN 2023, ICROS 2022, and HCI Korea 2022.
Proof of
craft.
Credentials earned along the way — the coursework and exams behind the practice.