Vasiliy Uvarov · Work recordBuilt. Shipped. Led.

As Chief Data & AI Officer at Altery, I lead a team of four data scientists and a data engineer, and I build and operate internal agent systems inside a UK electronic-money institution: systems that know where company context lives, call the right tools under real permissions, leave an audit trail a compliance officer will accept, and run at a cost that survives a budget review. The services call the OpenAI and Anthropic APIs, and I build them with Claude Code and Codex.

The FCA-approved EMD Individual standing is separate from that AI work. It concerns management of an electronic-money institution generally; it is not an AI qualification or an AI-specific accountability regime. The appointment was assessed against the Chief Product Officer seat and recorded against the firm. Supporting notification is available through the firm’s compliance function on request.

The platform layer. 230+ production-grade skills across 14 domains — compliance, engineering, marketing, data, QA, operations, agents, documentation, product, startup, document processing, developer tools, AI coding agents, and Altery regulatory — dispatched by an 8-router orchestration system. Routing is deterministic and auditable rather than model intuition: hand-authored routing maps, a machine-readable registry with explicit confidence thresholds, and a drift gate that fails the build when the checked-in skills graph differs from a fresh export. The library is mirrored publicly under MIT, so the structure can be inspected without an NDA.

The coordination layer. requirements-hub— a cross-repo coordination repo that makes a large service estate discoverable to humans and agents alike. Deterministic scanners profile each service’s APIs, databases and infrastructure into normalised records; deployment state is read from the GitOps source of truth rather than from memory; repo-local documentation coverage is tracked as a governance KPI instead of left to goodwill; and a platform-wide regulatory gap analysis keeps each gap categorised and remediation-tracked.

The agent services and operator layer. Enterprise-wide AI platform with governance across 7 departments — 20+ Custom GPTs and 9 Agent SDK apps in production, with near-universal engineering adoption. Agent-assisted KYB onboarding, a programme I led, saves 5+ hours per case; as at October 2026 it had run 800+ checks and ordered 500+ documents. The flagship agents are services, not prompts. A fraud and PII detection engine applies 40+ config-driven rules to production sign-up and sign-in logs, and I run it on exported logs when needed; its 293 tests include parallel-versus-single-pass equivalence checks. I also rebuilt a 78-node no-code support workflow as an asynchronous Python service, with OpenTelemetry, Prometheus, vaulted secrets and PII scrubbing. It has 170 tests and 43 golden cases, and it is not yet in production. I designed, built and reviewed both, with AI coding agents writing much of the code under my direction. Technical walkthrough and supporting evidence are available on request; test totals are not a measurement of answer accuracy.

Led the product and platform foundation for a regulated fintech and crypto-infrastructure business, and scaled it to €8-figure monthly GMV. Led Visa and UnionPay principal membership work, in-house clearing, multi-currency cards (GBP/USD/EUR), Apple Pay / Google Pay tokenisation, crypto-to-fiat ramps (TON / USDT / NOT) under 60 seconds, paperless proof-of-address in 29+ countries, and payout rails across 10+ markets.

Stood up the analytics and operating cadence from a blank page — a self-serve BI migration, an OKR cycle, seven cross-functional squads, and monthly company-wide demo days. CAC per transacting user fell roughly 2.5× over the period.

Partnered with an executive team to rebuild product and growth systems: UX audits and funnel tuning that roughly tripled onboarding conversion, and scoping discipline plus PM coaching that cut the feature backlog by more than half. Left behind a product-ops model — an experimentation pipeline, OKRs embedded in roadmap planning, and an org design spanning product, engineering and compliance — rather than a set of recommendations.

The client, its sector and its scale are covered by the engagement NDA. The underlying figures are available in a conversation under the same terms.

Owned onboarding and the merchant lifecycle for an EU and international B2B payments platform. Cut KYB onboarding from ninety days to twelve through automation and process redesign, and improved merchant time-to-revenue by seventy percent by simplifying the funnel. Introduced OKRs tied to activation, drop-off and LTV; backend optimisation cut transaction costs by 52%.

Led onboarding and master-data architecture for financial institutions and broker platforms. Replaced fifty percent of legacy dependencies — unlocking £1.7 million in annual savings and a thirty-five percent cut in onboarding abandonment. Rebuilt KYC/AML as modular, region-ready flows.

This role overlapped with the Taiger role below. Both date ranges are accurate: they ran concurrently during a relocation from Moscow to Singapore.

Owned solution design and go-to-market for AI-powered KYB and document-extraction tools. Closed £321K+ in Tier-1 bank deals through demo-led enterprise cycles — discovery, technical evaluation, deployment — and drove product-market fit for OCR/NLP compliance modules holding 90%+ recognition accuracy. Built a 25-plus lead pipeline in under six months and launched a bundled go-to-market with delivery partners.

The closest earlier analogue to the current role: scoping a document-extraction problem with a bank’s compliance team, then proving accuracy against their own documents.

Built and scaled an SME lending platform from ₽70 billion to ₽130 billion; cut origination time from fourteen days to under one via low-code orchestration. Deployed a hundred-plus RPA bots across SME onboarding and operations, optimising ninety-plus FTEs of process labour. Shipped AI-powered KYB with 92–94% OCR accuracy.

Oversaw a £100 million-plus IT portfolio across 21 teams and 230-plus engineers — CRM, onboarding, mobile, lending, and core systems. Prepared financial models and KPI projections for bank committees.

This role ended in October 2021, before the February 2022 sanctions regime.

Independently built astrology and divination product, combining product decisions, engineering, analytics and subscription delivery. The product has paying subscribers. Native iOS in Swift plus a Next.js web app, sharing a backend, localised into fourteen languages. Chart calculation runs on a deterministic VSOP87 ephemeris held to ±0.1° against JPL Horizons — not an LLM guessing at planetary positions. The build receipt covers the cosmic copilot native app + web app and is dated 21 May 2026.

Hallucination detection, citation-drift tracking, competitive intelligence, and recommendations for getting cited by answer engines. The eval discipline is the product: every claim an engine makes about a brand is graded against a source.

A Python pipeline ingests and normalises apartment listings; a Next.js and Firebase front end publishes them, tuned for answer-engine and search visibility. The point-in-time receipt covers the prime legacy homes repository and was measured 21 May 2026.