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

Target•Brooklyn Park, MN

3d•Hybrid

About The Position

Working at Target means helping all families discover the joy of everyday life. We bring that vision to life through our values and culture. As a Sr Engineer - Malware Reverse Engineering you will join a team supporting teams across our Cyber Fusion Center (CFC). This Malware Analysis role is not centered on manually reversing every instruction or task, but instead investigating, researching and implanting new ways we can leverage AI-assisted tooling to triage samples, validate machine-generated analysis and investigate complex or evasive malware where regular automation falls short. You will develop a strong foundation in reverse engineering while learning how to operate at high scale, analyze attacker tradecraft, think adversarial about both malware and analysis systems as well as translate reverse engineering insights into durable detections across the CFC.

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, gaps or adversarial manipulation in automated outputs. Refine analysis by guiding tools toward deeper behavioral understanding.
Triage and Prioritization at Scale: Analyze large sample sets and cluster malware into families and campaigns. Distinguish commodity noise from high-impact or novel threats. Escalate edge cases requiring deeper manual investigation.
Targeted Reverse Engineering: Perform focused reversing on critical code paths (i.e. loaders, unpacking routines, injection logic). Analyze obfuscation, packing and anti-analysis techniques. Investigate unusual or non-standard execution environments (custom VMs, staged payloads).
Exploit Awareness and Analysis: Recognize common exploitation patterns (memory corruption, logic flaws, sandbox escapes). Assist in reconstructing exploit chains and post-exploitation behavior. Support root-cause understanding for vulnerabilities observed in the wild.
Detection Development: Contribute to high-quality detection logic (YARA, behavioral rules, heuristics). Extract stable, meaningful indicators from reversed samples. Collaborate with detection engineers to ensure resilience against evasion.
Tooling and Pipeline Interaction: Work with automated analysis pipelines (static, dynamic, emulation). Assist in improving analysis workflows and signal quality. Leverage Python scripting to extend or customize tooling.