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 (Git Hub 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, Sage Maker) 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 B2 B Saa S environment is strongly preferred. Disclaimer: Please ignore the salary range provided.

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