GeoComply

Senior Mobile Security Engineer (Forensics)

GeoComply • VN
Hybrid
About GeoComply

We’re GeoComply! We are at the forefront of geolocation, cybersecurity, and anti-fraud innovation, developing and delivering cutting-edge technologies to help ensure regulatory compliance, combat bad online actors, alleviate user friction, and protect businesses from fraud.

Achieving significant business and revenue growth over the past three years and dubbed a tech “Unicorn,” GeoComply has been trusted by leading global brands and regulators for over ten years. Our compliance-grade geolocation technology solutions are installed on over 400 million devices and analyze over 12 billion transactions a year.

At the heart of it all is the people, united by a deep commitment to problem-solving and revolutionizing how people and businesses use the internet to instill confidence in every online interaction. With teams across five countries, three continents, and a global customer base, we have no plans to slow down.

This is a pivotal senior role placing you on the front lines of protecting millions of users from sophisticated mobile fraud and adversarial attacks. As a Mobile Security Engineer (Forensics), you will design, build, and operate systems that investigate and attribute malicious activity across Android and iOS.

You will work across the full forensic lifecycle—from secure on-device signal collection and evidence preservation to large-scale analysis, attacker behavior reconstruction, and incident response. Operating at the intersection of mobile engineering, security, and data, you will uncover emerging fraud and spoofing techniques, strengthen detection systems, and help protect users at scale.

Key Responsibilities

  • Analyze large-scale datasets and fraud incidents to uncover attack patterns, fraud clusters, and evolving adversarial behavior, including reconstructing attacker techniques and execution paths.
  • Partner with the mobile development team to design and implement mobile SDK components to securely collect forensic-grade signals, enabling attribution of location spoofing, emulator abuse, rooted/jailbroken environments, and other environment manipulation.
  • Execute and lead deep technical research into emerging mobile fraud and evasion techniques, translating findings into actionable forensic indicators.
  • Build and mature end-to-end incident response capabilities across the stack, partnering with Data Science and ML teams to translate forensic insights into technical features, rules, and detection logic.
  • Provide technical guidance and mentorship to junior engineers on best practices in mobile security, forensics, and data analysis.
  • Who You Are

  • Deep passion for investigating security incidents, hunting attackers, and uncovering sophisticated fraud, spoofing, and abuse patterns, with a strong curiosity for understanding how adversaries operate and evade defenses.
  • 4+ years of progressive, hands-on experience in security, forensics, or offensive security, with a proven track record of delivering high-impact security solutions.
  • Bachelor's degree in Security Engineering, Computer Science, or Computer Engineering is required; advanced technical degree is a plus.
  • Demonstrated expertise and practical application of data analysis (SQL, data modeling, feature extraction) in security investigations.
  • Familiarity with data science concepts and the role of ML in detection systems
  • Strong English communication skills, with the ability to clearly document findings and explain technical investigations to both technical and non-technical audiences.
  • Plus point

  • Experience with mobile development (Android, iOS, or cross-platform).
  • Familiarity with mobile security and forensics, including: Root / jailbreak detection and evasion techniques
  • Emulator and virtualized environment detection
  • Location spoofing and geolocation integrity validation
  • Device attestation, TEE, Secure Enclave, and hardware-backed security
  • Interest in incident response, threat research, or adversarial analysis.