Our client is a general leader in Telecom Fraud Management. The client's winning aspiration is to empower every digital journey to be fearless, seamless, and fraud-free.We are looking for a Technical Product Manager (TPM) who can serve as the bridge between advanced engineering and real-world fraud management outcomes. The TPM will work at the intersection of technology and product strategy, driving the evolution of our platform from traditional rules-based and AIML capabilities - a system that detects, investigates, and resolves fraud with minimal human intervention.KEY RESPONSIBILITIES:1. Product Strategy & Roadmap• Define and own the technical roadmap for FMS, aligning with company strategy, Technology evolution and market trends.• Evaluate and prioritise product capabilities based on customer value and business impact.• Drive 0-to-1 feature development as well as the scaling and optimisation of product capabilities.2. Technical Leadership & Cross-Functional Collaboration• Collaborate daily with Engineering, platform architects, and UX designers to translate product requirements into technical specifications.• Deeply understand product lifecycles• Lead technical discovery sessions, write detailed PRDs with acceptance criteria, and makeinformed trade-off decisions• Partner with architects to define a scalable, secure, and cloud-native solution.3. Customer &Domain; Expertise• Develop deep expertise in telecom fraud typologies — bypass fraud, subscription fraud, roaming fraud, Wangiri, SIM swap, Robocalling, Spamming,



Smishing and emerging attack vectors.• Conduct regular customer interviews and advisory board sessions to understand evolving fraud patterns and operational pain points.• Translate customer needs into AI-powered product solutions that reduce false positives, accelerate investigation time, and improve fraud recovery rates.4. Data-Driven Product Management• Define and track key product metrics• Use product analytics, A/B testing, and model performance dashboards to guide iteration and prioritisation.• Own revenue and adoption accountability for features within FMS.DESIRED CANDIDATE PROFILE:• Technical Credibility: Comfortable discussing model architectures, API designs, data pipelines, and system scalability with engineering teams — without needing to write the code.• Fraud Domain Expertise: Prior experience in fraud management, risk, or cybersecurity — preferably in telecom, fintech, or enterprise software — is strongly preferred.• Execution Excellence: Track record of driving products from concept to launch, owning metrics, and iterating based on data. Not afraid to sign up for results.• Communication & Influence: Exceptional ability to synthesise complex technical and business concepts for diverse audiences — from C-suite to engineers to customers.• Customer Obsession: Relentless focus on understanding and solving real customer problems,



backed by structured research and empathy.Required:• Deep familiarity with fraud detection system architectures: real-time event streaming, rule engines, threshold management, case management, and reporting.• Understanding of telecom data structures — CDRs, signalling data (SS7, Diameter), network topology — and how they are used for fraud pattern identification.• Knowledge of fraud investigation workflows: evidence collection, case lifecycle management, escalation paths, and regulatory reporting requirements.• Awareness of key compliance and regulatory frameworks relevant to telecom fraud: GDPR, OFCOM, FCC, GSMA guidelines, and local CSP obligations.• Familiarity with integration patterns between FMS and adjacent systems: mediation platforms, BSS/OSS, network probes, and third-party threat intelligence feeds.Preferred / Bonus:• Experience working in or with AI coding environments (GitHub Copilot, Cursor, etc.) to accelerate product discovery.• Exposure to graph-based fraud detection, network analysis, or entity resolution systems.• Understanding of MLOps tooling (MLflow, Kubeflow, SageMaker) and model monitoring in production.• Experience with NLP for telecom data, CDR analysis, or voice/SMS fraud pattern recognition.EDUCATIONAL QUALIFICATIONS & EXPERIENCE:• Graduate / Post Graduate in Engineering (Computer Science, Data Science, or related field) from a premier institute.• Minimum 8–12 years of industry experience, with at least 4–5 years in a product management role.• Prior experience in telecom, fraud management, cybersecurity, or a data-intensive B2B SaaS environment is strongly preferred.Disclaimer: Please ignore the salary range provided.

📌 Technical Product Manager - Fraud Management System (España)
🏢 Mbr Partners
📍 España