Drimva

Two Six Technologies

Vulnerability Research Analyst

$158K–$237K

Linthicum, Maryland +1 · Full-time · Posted Oct 15, 2026

Location
Linthicum, Maryland
Customer Site - Linthicum, MD
Experience
Experience in vulnerability research, static source code analysis, reverse engineering, or software security audits; no number of years stated.
Education
Degree in Computer Science, Computer Engineering, Information Security, or equivalent practical experience.

About the job

Conducts software vulnerability research on extracted source code and binaries, evaluates AI-assisted detection tools, and assesses the root causes and exploitability of software flaws.

What you'll do

  • Perform static and dynamic vulnerability analysis on source code repositories and firmware images.
  • Use AI-guided fuzzing and automated detection tools, then validate findings by tracing code execution.
  • Create detection rules and signatures, automate regression testing, and present risk assessments and metrics.

What they ask for

  • Active US Security Clearance of Top Secret/SCI with polygraph; must be willing to obtain and maintain a Polygraph clearance.
  • Degree in Computer Science, Computer Engineering, Information Security, or equivalent practical experience.
  • Experience in vulnerability research, static source code analysis, reverse engineering, or software security audits.
  • Understanding of memory management, pointer arithmetic, common software security flaws, and automated code analysis concepts.

Nice to have

  • Experience authoring or tuning rules with CodeQL, Semgrep, or Tree-sitter parsers; firmware emulation experience.
  • Experience with custom test harnesses, machine learning for bug discovery or code analysis, or DoD/IC vulnerability assessments.

Pay

$157,847 — $236,771 USD annualized base salary

Tools

CodeQL, Semgrep, Tree-sitter, QEMU, Unicorn Engine, Avatar2, Ghidra, IDA

AI focus

Deploy AI-guided fuzzing and automated vulnerability detection; familiarity with AI-driven automation tools and machine learning applications in automated bug discovery or AI-assisted code analysis.

Model-written summary · the original posting is authoritative

First seen Oct 29, 2026 · Last verified Nov 5, 2026 (UTC)