Product leader & engineer at the intersection of B2B FinTech and AI. Director of Product at Cinimex Group (KZ · RU) by day; shipping AI-native systems and infrastructure on GitHub to stay close to the metal.

ORCID Google Scholar LinkedIn

• 20 years in B2B FinTech and banking platforms
• Grew the practice I lead from 0ドル.2M → 15ドルM annual revenue and 9 → 150+ specialists
• 8 national award-winning projects across TAdviser IT Prize, CNews Innovation, FINNEXT, Best ESG, "Project of the Year"
• Payment Hub — large-scale RF cross-border infrastructure (TAdviser IT Prize 2023) · VTB API Platform — 2,000+ internal teams, 700+ APIs (CNews Innovation 2023) · OpsNext — 99% STP across 5.4B annual transactions · Strela — first corporate-deal personalization system in RF (FINNEXT 2025)
• IEEE Senior Member (#99277800) · Patent holder (RU 2012616579 — Cinimex Test Tool, deployed in 6 of the top-10 RF banks) · Author of Digital Bank (Amazon, 2023)

Plus a long-running side project from 2018: backtestportaa — Java tool for back-testing investing portfolios with technical indicators.

Public, large-scale collaborations across borders:

• Cinimex Group operates across CIS and Southeast Asia with regional offices including a dedicated Kazakhstan office — gives the team a working footprint across multiple regulatory perimeters
• Volkswagen Group AG — joint dealer-network digital ecosystem and IDP platform with the Berlin office (Kubernetes / microservices, 40-person cross-border team)
• Alibaba / AliPay — adoption of ISO 20022 for cross-border payments processed through Russia
• Bank of Russia — first CBDC (digital ruble) transactions in the country; first B2B smart contracts in construction (Mosinzhproekt); contributor to CBDC technical standards
• Direct payment channels built into Payment Hub: China (UnionPay, CIPS), India (NPCI, RuPay), Vietnam, Bangladesh — covering ~60% of RF cross-border trade with the Asian region
• McKinsey & Company · EPAM Systems — joint delivery on enterprise digital-transformation programs
• Began my career at Exigen Services (now Emergn) — at the time a top-4 outsourcing firm globally, US clients, English-medium delivery

• Start from the user, not the framework. Every project begins with "what does this make easier for the person using it?" — only then does the stack become a question.
• Ship narrow, then expand. A prototype that does one thing well beats a backlog of half-built features. If real users don't pull on a feature, it doesn't get built next.
• Defaults are policy. Cosmetic choices — copy, ordering, what's pre-selected — have product consequences. They get the same care as architecture.
• Documentation is part of the deliverable. Every project ships with a real README, architecture notes, and CI from day one. If a reviewer can't understand the system from the repo, the system isn't done.
• AI in the loop, not in the way. Production tooling, not a demo — see the patterns below.

Patterns I reach for:

• Discriminated-union message protocols — every cross-process message is a member of one TypeScript union; adding one without handling it doesn't compile (45-type union in ai-tab-optimizer)
• Per-batch provider failover — Claude Code → Codex CLI → heuristic, decided per batch by a small policy module; transient rate limits don't kill long autonomous runs
• Three-tier model dispatcher — cheap classification → medium reasoning → expensive synthesis, picked automatically per task (clawden-ai's OmniRoute)
• Stop-and-resume autonomous runs — run state in SQLite with per-tab status, pending queue, partial results, accumulated metadata; survives reload mid-1000-tab sweep
• Knowledge-graph memory — LightRAG over an Obsidian vault, fed continuously by event-driven bridges; replaces "chat history" as long-term context
• Multi-channel data planes with explicit ownership boundaries — no silent rewriting between layers (ghostroute's A/B/C channels)
• MCP-first context engineering — custom MCP servers (lean-ctx) and tool-search budgets to keep agentic dev sessions within cache windows

Tooling

• AI runtime — Claude Code · Codex CLI · OpenClaw · MCP servers · LightRAG · DeepSeek · Yandex AI Studio · Anthropic / OpenAI APIs
• Niche stack — sing-box · xray · Reality protocol · Hetzner · Telethon · ASUS Merlin
• Languages & web — TypeScript · Python · Java · React · Vite · FastAPI · Tailwind · shadcn/ui · Docker · SQLite · PostgreSQL · Linux

• Currently focused on: building AI-native systems where digital workers own entire operational functions — autonomous teammates that observe, decide, escalate, and report, rather than chat assistants triggered on demand. The goal is measurable business outcomes: faster deal cycles, lower OPEX, and human teams freed for higher-leverage work. Applied to B2B FinTech operations, CBDC and tokenized settlements, and cross-border payment infrastructure. Published expert profile and articles on this thesis at RBC Companies
• Author of Digital Bank (Amazon, 2023) — handbook on banking digital transformation
• IEEE Senior Member (#99277800) · Skolkovo Foundation expert since 2023 · FSI grant jury member
• 10+ peer-reviewed papers indexed at Google Scholar and ORCID
• Yandex Practicum — System Architect program (2025) · Karpov.Courses — ML & System Design · GoPractice — Product Management Simulator · ICAgile Certified Professional
• Languages: Russian (native), English (C1)
• Open to interesting conversations on LinkedIn

Profile views Followers Total Stars

_{This profile is maintained at eiler2005/eiler2005.}