Software Engineer II - Insider Risk

As organisations face increasingly sophisticated social engineering and insider threats, the very foundation of trust,the employee identity,is under attack. Abnormal’s Identity Security team is building a groundbreaking product to detect and prevent fraudulent employee identities, specifically targeting high-stakes threats like infiltrators seeking to funnel funds through deceptive employment.

You will build identity verification and fraud detection systems to scrutinise candidate data during the application process.

Responsibilities:

• Build identity verification and fraud detection systems to scrutinise candidate data during the application process.
• Develop sophisticated correlation engines that match candidate details (IPs, phone numbers, email history, resume metadata) against known indicators of fraudulent or state-sponsored activity.
• Create high-availability pipelines that ingest and analyse signals from application tracking systems (ATS), identity providers, and external risk intelligence.
• Ship automated guardrails that flag high-risk candidates in real-time, enabling security teams to act before an infiltrator is onboarded.
• Drive 0→1 iteration: prototype quickly, test fraud detection assumptions, learn from emerging threat patterns, and scale simple, effective solutions.
• Collaborate across security, platform, and data teams; write and review technical designs; and participate in core SDLC rituals.

Requirements:

• 2+ years building software applications.
• Experience productionizing large-scale, data-intensive systems.
• High velocity and creativity in solving technical challenges related to fraud detection and pattern matching.
• Experience & desire to adopt & improve AI-native development workflows.
• Strong debugging skills with logs, metrics, and behavioural signals.
• Ability to translate complex security and business requirements into high-quality software.
• Ability to independently solve complex problems and work cross-functionally.
• BS in CS/SE/IS or a related field.

Nice to Have:

• Experience with Go and Python.
• Experience in fraud detection, identity verification, or anti-money laundering (AML) systems.
• Background in cybersecurity, specifically focused on insider threats or nation-state actor TTPs (Tactics, Techniques, and Procedures).
• Experience with big data, statistics, and ML for identity/behavioural risk modelling and anomaly detection.

Benefits:

• Base salary range: $149,200-$214,500 USD
• In addition to base salary, this role may be eligible for bonus or incentive compensation, equity, and a comprehensive benefits package.