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Fintech Hiring Packet

Mahmood Asadi — AI Orchestrator & Product Leader

Fintech platforms, broker workflows, governed AI systems, and audit-ready delivery — owned concept to deployment

Based in Yerevan, Armenia — serving global clients

Target Roles

  • Fractional CPO — product direction and delivery for fintech teams without a full-time exec
  • Head of AI Strategy — governance model, risk posture, and roadmap for regulated AI adoption
  • Lead Fintech Architect — broker platforms, trading infrastructure, and audit-grade systems
  • Founding Engineer / Technical Lead — AI governance or trading infrastructure
Where I've built:fintech · education · manufacturing · enterprise platforms
What stays constant:governance-first design, reproducible verification, audit-ready evidence

What I Do

  • –Build fintech systems end-to-end — broker platforms, trading interfaces, real-time risk surfaces, and audit-grade operator workflows
  • –Ship at startup speed with strong engineering hygiene: tests, CI gates, typed interfaces, and deterministic evidence where it matters
  • –Design AI features with clear decision boundaries: recommendations, approvals, traceability, and fail-closed paths before autonomy

Flagship Case Studies

Truvesta

Dealing-desk intelligence platform — Fintech
Problem: Forex/CFD brokers needed fast, explainable risk signals and defensible decision trails — but their tools were fragmented dashboards on legacy systems with governance enforced only at the app layer.
Key Constraints:
  • •Audit trail must be tamper-evident and verifiable by a third party
  • •Shadow mode is a hard invariant — system observes, never executes trades
  • •Async audit writes rejected: deterministic traceability or nothing
Key Decision: Chose hash-chained, synchronous audit events with DB-level immutability triggers over async logging. Slower per-write, but the audit chain is provably complete and tamper-evident — a requirement in regulated brokerages.
Outcome: Replaced 3–4 fragmented dealer tools with one audit-grade platform. 14+ modules, 50+ screens, 3 user roles. Shipped in 3 weeks. Tamper-evident audit chain verifiable by any third party. Zero shortcut paths.
📎 Live demo + full architecture walkthrough available

Ardura

Broker CRM with AI-driven churn prediction — Fintech
Problem: Broker CRMs fail at retention: they either ignore AI signals or pipe them straight to automation without operator judgment — creating liability when models drift and silent churn when they don't.
Key Constraints:
  • •AI predictions must never auto-execute actions on clients
  • •Every recommendation must show its reasoning (no black-box outputs)
  • •Governance components reused from Truvesta without cutting safety
Key Decision: Built a human-in-the-loop approval queue where every AI-driven retention action requires explicit operator sign-off with full attribution. Traded automation throughput for auditability — the right tradeoff in regulated client communications.
Outcome: Increased retention intervention quality while eliminating autonomous risk. Full CRM shipped in 2 weeks. Complete lifecycle view: acquisition → engagement → risk → retention. Zero autonomous actions — every intervention is operator-approved with auditable decision chain.
📎 Architecture doc + evaluation trace samples available on request

Skills Snapshot

Systems

Distributed systems, multi-tenant architecture, event-driven design, state machines

Governance

Tamper-evident audit trails, hash-chained logs, fail-closed policy engines, evidence packs

Data

PostgreSQL (audit-grade schema design), Prisma, immutable event modeling, traceable state transitions

CI / Quality

CI gates that falsify invariants, drift detection, shadow-mode testing, reproducible evidence

Frontend

Next.js, TypeScript, Tailwind, Framer Motion, real-time WebSocket UIs

AI Integration

Agent orchestration, RAG pipelines, human-in-the-loop patterns, evaluation traces

Proof Links

Capabilities →Fintech Work →Case Studies →Technology Stack →Live Governance Demo →

Ready to talk?

Send a role, team context, or interview brief. I can respond with relevant case-study proof and availability.

Email Mahmood →LinkedIn →

hello@asadi.ai · LinkedIn · asadi.ai