AI Process Owner – Transaction Monitoring, Customer Lifecycle

Finom

. Own AI implementation for transaction monitoring alert resolution from identifying high-value manual steps through production deployment .

Posted 9/22/2026full-timeRemote • Poland, Netherlands, SpainMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in AI implementation for transaction monitoring and alert resolution, with a strong focus on data analysis, AML frameworks, and process ownership. Capable of collaborating with cross-functional teams to enhance operational efficiency and customer experience.

Highest-signal resume keywords

AI ImplementationTransaction MonitoringData AnalysisAML FrameworksSQL

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

AI ImplementationData AnalysisTransaction MonitoringAlert ResolutionModel ValidationPythonSQLKYC/CDDSAR/STR ReportingThreshold Optimisation

Soft Skills

Customer-Minded ApproachStructuredPragmaticProcess Ownership

Tools & Technologies

DatabricksMetabasePower BI

Industry Keywords

FintechBankEMIPSPAMLRegulatory RequirementsModel Risk ManagementAI Governance

Tech Stack

Tools & technologies

PythonSQL

About the role

Key responsibilities & impact

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

What you’ll need

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

Comp & perks

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