Sr Engineer - Malware Reverse Engineering (AI-Augmented Analysis)

Target•Brooklyn Park, NC

4d•Hybrid

About The Position

Target Cybersecurity is seeking a Sr Engineer - Malware Reverse Engineering to join their Cyber Fusion Center (CFC). This role focuses on leveraging AI-assisted tooling to analyze malware at scale, validate machine-generated analysis, and investigate complex or evasive threats. The engineer will develop strong reverse engineering skills while learning to analyze attacker tradecraft, think adversarially, and translate insights into durable detections.

Requirements

4 year degree or equivalent experience
5+ years of software or security engineering experience preferably in malware labs, CTFs or with personal research projects
Demonstrated understanding of reverse engineering concepts (x86/x64, assembly, calling conventions)
Familiarity with common malware techniques (packing, persistence, process injection)
Demonstrated programming knowledge in C/C++ and Python
Familiarity with YARA or other detection frameworks
Experience with tools like Ghidra, IDA Pro, Binary Ninja or similar
Exposure to dynamic analysis (debugging, sandboxing, instrumentation)
Understanding of OS internals (Windows or Linux), including processes, memory, and system calls
Basic networking knowledge (protocols, common attack surfaces)
Ability to reason about unfamiliar code and derive behavior from partial information
Basic knowledge of exploitation concepts (i.e. buffer overflows, ROP)
Curiosity when things don’t match expectations—willingness to dig deeper and analyze
Comfort working with incomplete or noisy data at scale
Willingness to rely on automation without blindly trusting it
Ability to critically evaluate machine-generated analysis
Interest in how adversaries may evade or manipulate automated systems
Maintains technical knowledge within areas of expertise
Stays current with new and evolving technologies via formal training and self-directed education

Responsibilities

AI-Augmented Malware Analysis: Review and validate AI-generated static and dynamic analysis results, identify inaccuracies or adversarial manipulation, and refine analysis to guide tools toward deeper behavioral understanding.
Triage and Prioritization at Scale: Analyze large sample sets, cluster malware into families and campaigns, and distinguish commodity noise from high-impact threats.
Targeted Reverse Engineering: Perform focused reversing on critical code paths (loaders, unpacking routines, injection logic), analyze obfuscation and anti-analysis techniques, and investigate unusual execution environments.
Exploit Awareness and Analysis: Recognize common exploitation patterns, assist in reconstructing exploit chains and post-exploitation behavior, and support root-cause understanding for vulnerabilities.
Detection Development: Contribute to high-quality detection logic (YARA, behavioral rules, heuristics) and extract stable indicators from reversed samples.
Tooling and Pipeline Interaction: Work with automated analysis pipelines, assist in improving analysis workflows, and leverage Python scripting to extend or customize tooling.