AI Process Owner – Transaction Monitoring, Customer Lifecycle

Job not on LinkedIn

🔥 7 minutes ago

🌐 Poland, Netherlands, +1 more countries – Remote

🇵🇱 Poland – Remote 🇳🇱 Netherlands – Remote 🇪🇸 Spain – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 Artificial Intelligence

👻 Ghost score 16%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Finom

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 2019

💳 Fintech

💸 Finance

🤝 B2B

Fintech • Finance • B2B

Finom is a fintech company offering comprehensive financial services for SMEs, freelancers, and companies. The platform provides tools for invoicing, expense management, and easy online account opening with added benefits like cashback and international IBAN accounts. Finom ensures data security through partnerships with banks like SolarisBank and Treezor, making it a fast and reliable service for business financial management.

📋 Description

• Own AI implementation for transaction monitoring alert resolution from identifying high-value manual steps through production deployment • Understand the alert resolution process from pickup to false positive, true positive, or offboarding • Build AI-driven investigation capabilities for customers, suspicious transactions, and behavioural and network patterns • Build and iterate AI agents that replace manual analyst work with clear boundaries, escalation logic, and audit trails • Redesign alert resolution around automation, validation, human review, and quality evidence • Define and document the AI/AML boundary for risk management, audit, and regulators • Support and upskill analysts transitioning to model and output validation • Analyse alert and customer data to identify inefficiencies, false-positive drivers, and automation opportunities • Partner with AI, Data, Engineering, Product, and risk management teams to translate operational and AML needs into technical requirements • Improve customer experience by reducing unnecessary touchpoints and resolution delays • Own procedures, decision logic, model rationale, and controls to audit standards • Track cycle time, alert backlog, AI resolution share, decision quality, analyst capacity, and customer-facing impact

🎯 Requirements

• 3+ years of experience in a fintech, bank, EMI, or PSP environment in transaction monitoring and AML • Hands-on experience in first line of defence alert resolution • Solid understanding of AML frameworks and practical alert resolution • Experience implementing AI in projects • Understanding of AI limitations within transaction monitoring and regulatory requirements • Strong data analysis skills • Comfortable with Databricks, Metabase, and Power BI • SQL is a real advantage • Customer-minded approach • Structured, pragmatic, and comfortable owning a process end to end • Professional fluency in English • Nice to have: experience building or deploying AI agents or LLM-based workflows in a regulated or operational setting • Nice to have: exposure to model validation, model risk management, or AI governance • Nice to have: transaction monitoring vendor systems and rule tuning / threshold optimisation • Nice to have: periodic reviews, KYC/CDD, or ongoing customer due diligence • Nice to have: SAR/STR reporting • Nice to have: Python or similar for data work and prototyping

🏖️ Benefits

• Continuous personal and professional development opportunities • Flexibility to travel and work remotely or in a hybrid model across Europe • Stock Options Program available to every team member • Supportive, friendly, modern, and eco-conscious corporate culture • Work & Swim Program: one month in a corporate apartment in Cyprus • International, remote-friendly team • Room to grow and expand scope across the customer lifecycle • Direct collaboration with Compliance, Risk, Data, Product, and Engineering leadership