Sr. Security Engineer - FRM

Krafton; Bengaluru; Presencial; INR 1.800.000 - 3.000.000; Jornada completa

Descripción de la vacante

Krafton is seeking a skilled Fraud Risk Manager to lead real-time detection and monitoring across payment-heavy systems in Bengaluru. You will design risk scoring, rules engines, and ML-driven detection to protect against fraud and ensure regulatory compliance.

You will work with Python and SQL on large datasets, collaborating with cross-functional teams to implement robust controls and incident response workflows. Prior experience in fintech or payments is highly valued.

Formación

• 4-7 years of experience in Fraud Risk Management, Trust & Safety, or Risk Engineering.
• Hands-on experience building or operating real-time fraud detection and transaction monitoring systems.
• Strong understanding of risk scoring, rules engines, and ML-based fraud detection approaches.
• Experience with payment flows, UPI, wallets, or similar transaction-heavy systems.
• Familiarity with regulatory requirements around fraud and risk controls (NPCI, RBI, sanctions/watchlist screening, STR) and reporting.
• Proficiency in Python or a similar language; comfortable with SQL and large datasets.

Responsabilidades

• Lead development and operation of real-time fraud detection and monitoring capabilities.
• Translate emerging fraud patterns into actionable detection logic and rules.
• Own risk controls and review/escalation processes from day one.
• Collaborate with product and engineering to ensure compliance with NPCI/ RBI guidelines.

Conocimientos

Python

SQL

Real-time systems

Fraud analytics

Herramientas

Case management tools

Descripción del empleo

Key Responsibilities :

• 4-7 years of experience in Fraud Risk Management, Trust & Safety, or Risk Engineering, ideally in fintech, payments, or banking
• Hands-on experience building or operating real-time fraud detection and transaction monitoring systems
• Strong understanding of risk scoring, rules engines, and/or ML-based fraud detection approaches
• Experience working with payment flows, UPI, wallets, or similar transaction-heavy systems
• Familiarity with regulatory requirements around fraud and risk controls - NPCI, RBI, sanctions/watchlist screening, suspicious-transaction reporting, and comparable regimes
• Proficiency in Python or a similar language; comfortable working with SQL and large transactional datasets
• Strong analytical mindset, with the ability to translate emerging fraud patterns and typologies into actionable detection logic
• Comfortable owning a control that only works if someone actually works it - the review queue and escalation path are real from the day you’re behind them
• Experience with UPI/TPAP ecosystems or NPCI-regulated payment products is a plus
• Experience with case management tools and fraud investigation workflows is a plus
• Exposure to machine learning-based risk models in production, including model governance and drift monitoring, is a plus
• Prior experience supporting statutory or regulatory audits related to fraud or risk controls is a plus