Software Engineer II - Entity Intelligence

Responsibilities

• Design, build, and operate AI-native detection systems focused on impersonation and fraud prevention
• Own detection projects end-to-end, from initial design and implementation through rollout and monitoring
• Analyze missed attacks to identify underlying patterns and translate them into system-level detection enhancements
• Write and tune detection logic using scored signals and attributes to minimize false positives
• Build and evaluate LLM-based detection agents, measuring precision and recall rigorously
• Participate in on-call rotations to debug and resolve customer escalations

Requirements

• 3+ years of professional software engineering experience with a track record of shipping production systems
• Strong software engineering fundamentals, including data structures, algorithms, and system design
• High proficiency in Python
• Strong data analysis skills and proficiency in SQL for reasoning over large datasets
• Experience with AI-native development and an interest in building LLM-powered systems
• Ability to own projects with initial ambiguity and communicate status clearly

Preferred Qualifications

• Experience with distributed systems, high-throughput pipelines, or large-scale data stores (e.g., PostgreSQL, Kafka, Spark)
• Background in security, threat detection, anti-abuse, or fraud detection
• Experience with ML or LLM evaluation, including precision/recall tradeoffs and prompt iteration
• Familiarity with domain/DNS concepts or identity and impersonation signals
• Experience in a fast-paced, high-growth startup environment

About the Company

Abnormal AI builds AI-native security products that stop cybercrime and protect critical communications, identities, and infrastructure in the cloud. Our platform operates at high scale and low latency to defend enterprises against sophisticated attacks.