About The Position

Coinme’s Payments & Risk team keeps transactions safe, disputes defensible, and fraud controls sharp as we scale across consumer and platform channels. The Director of Payments & Risk owns that mission end to end: the fraud defense strategy, the AI-augmented operation that executes it, and the team that runs it. This is a player-coach role. You set the defense architecture across fraud vendors, card processors, and banking partners, working closely with internal stakeholders such as Compliance, Product and Engineering and you keep enough hands-on depth to read raw logs and question what a rule actually did. You build and govern AI-assisted workflows that carry much of the operational load, and you develop the analysts and scientists who operate them. Decisions here are made on evidence, at speed, and must survive audit, and the function you build must not depend on any single person, including you. You own the economics of risk: losses, recoveries, and the customer friction in between.

Requirements

  • 8+ years in payments risk, fraud, or dispute operations within financial services or cryptocurrency, including 3+ years leading a risk, fraud, or trust and safety function, ideally at a crypto exchange or on/off-ramp.
  • Card-rail mechanics (authorization and decline flows), chargeback and representment economics, Visa and Mastercard dispute rules and card-network monitoring programs, working knowledge of ACH and real-time rails, and fluency in crypto-side risk (wallet behavior, on-chain flows, cash-out typologies).
  • Extensive hands-on administration of modern fraud prevention platforms (Sardine, SEON, Sift, Kount, Forter, or similar), including rule authoring, shadow-versus-live testing, and the instinct to reverse-engineer what a rule actually does rather than trust its label.
  • Strong SQL and comfort in log and observability platforms and analytics tooling; you answer your own questions without waiting on an analyst.
  • You have built or governed AI-assisted operational workflows and can speak concretely about what you automated, what guardrails you set, and what you deliberately kept human. Aptitude is assessed in a working session.
  • You document, cross-train, and design systems that outlive your tenure; the functions you leave keep running without you.
  • You change processes you don’t own, fixing root causes in other teams’ systems rather than building permanent workarounds.
  • You have hired, developed, and retained analysts, and you can lead a team through AI-driven change in how the work itself gets done.
  • Evidence discipline over convenient narratives, conservative and defensible metrics over optimistic ones, protection of good customers weighed as seriously as fraud losses, and clear communication to both technical and executive audiences.

Nice To Haves

  • Direct experience with the Sardine platform and/or card processor integrations (TabaPay or similar).
  • Threat-informed defense frameworks (MITRE ATT&CK, AADAPT, F3) applied to fraud.
  • Blockchain analytics tooling (TRM Labs, Chainalysis, Elliptic) and wallet-clustering investigations.
  • BSA/AML and SAR familiarity, including SAR-aware evidence handling and partnering with compliance on account lock and reactivation policy.
  • Experience building with LLM agent frameworks (Claude Code, agent SDKs) or workflow-automation platforms.
  • Modern data-stack familiarity: dbt, warehouse modeling, product analytics.
  • Certifications (CFE, CAMS, FRM) or an advanced degree in a relevant field.

Responsibilities

  • Own the fraud risk strategy and the end-to-end defense architecture across the payments stack: vendor risk engines, internal controls, processor-level gates, and partner-bank requirements, with a current map of which system makes which decision.
  • Run the detection portfolio as a measured system: rules, thresholds, models, and velocity limits tuned against quantified false-positive versus fraud-capture tradeoffs, with disciplined change control and post-change monitoring.
  • Own the chargeback and dispute program economics: representing strategy, pre-dispute deflection signals (Ethoca, Verifi RDR, Compelling Evidence 3.0), win-rate and net-recovery reporting, and card-network monitoring standing.
  • Lead fraud investigations and incident response with evidence-first discipline: reconstruct the decision trail across vendor logs, application telemetry, and processor responses before assigning a disposition; distinguish system defects from legitimate controls; defend legitimate declines against pressure to override; and turn incidents into durable fixes.
  • Design and govern AI-native risk operations: agentic workflows for queue triage, decline forensics, fraud-ring detection, chargeback evidence assembly, and scheduled monitoring, with governance to match (QA gates before anything ships externally, human-in-the-loop checkpoints on account-level actions, auditable reasoning trails, and explicit boundaries on what automation may decide).
  • Build and develop the team: hire, coach, and grow risk analysts and scientists, and train them to operate and extend the AI-assisted workflows, with documentation and runbooks treated as first-class deliverables.
  • Drive root-cause fixes across the entire payment flow and customer journey: when a risk gap lives in another team’s system (compliance workflows, account lifecycle, internal tooling), own the influence campaign to fix it there instead of compensating downstream, and partner closely with compliance on the fraud/AML seam.
  • Manage the vendor and partner ecosystem at both levels: hands-on (rules, integrations, data quality) and commercial (SLAs, escalation paths, roadmap influence), and coordinate risk posture with processors, sponsor banks, and platform partners.
  • With a strong bias for action, report to executives on key risk mitigating actions to reduce risk exposure and loss, performance and risk metrics , with the ability to go beyond headline fraud rates: loss by channel, decline precision and false-positive cost, dispute win rates, automation coverage, and time-to-disposition, connecting risk decisions to profitability.
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