Job Description

Our client is a global 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 make
informed 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.