Sr. Cyber Engineer (AI)

Description of Task to be Performed:

We are seeking a Senior AI Engineer with deep experience in vulnerability research, reverse engineering, and automated exploit discovery. In this role, you will build advanced AI-driven systems to analyze binaries, discover flaws, and support secure engineering across complex environments. You will work at the intersection of security research, machine learning, and large-scale automation—designing tools that push the boundaries of modern vulnerability detection.

Key Responsibilities

• Lead research and development of automated systems for reverse engineering, including static, dynamic, and symbolic analysis workflows.
• Create tools to analyze compiled code, firmware, protocols, and novel architecture.
• Collaborate with VR researchers to convert cutting-edge techniques into scalable AI-driven capabilities.
• Build pipelines for ingesting binaries, disassembling, performing feature extraction, and training ML models.
• Perform hands-on reverse engineering of complex software to validate and improve AI-based approaches.
• Integrate LLMs and multimodal models into security workflows (e.g., code reasoning, decompilation assistance, exploit surface mapping).
• Document methodologies, findings, and architectures for internal engineering and security teams.
• Mentor junior engineers and guide cross-functional research initiatives.

Required Qualifications:

• 7+ years of experience in vulnerability research, reverse engineering, or low-level systems security.
• Strong proficiency with reverse engineering tools such as IDA Pro, Ghidra, Binary Ninja, Frida, or similar.
• Expert knowledge of exploit classes, memory corruption, program analysis, and OS-level internals.
• Professional experience building or integrating ML/AI systems, including transformer-based models or code-intelligence architectures.
• Proficiency in Python and at least one low-level language (C/C++, Rust, or Assembly).
• Strong understanding of binary formats (ELF, PE), calling conventions, and compiler behaviors.
• Experience with static analysis, dynamic instrumentation, fuzzing frameworks, or symbolic execution tools
• Clearance: Active TS/SCI Clearance with CI Polygraph 

Preferred Qualifications:

Experience developing AI/ML models that assist in binary analysis, vulnerability detection, and exploit pattern identification.
Experience training or fine-tuning ML models for code or binary analysis.
Familiarity with reinforcement learning, program synthesis, or neurosymbolic reasoning.
Experience analyzing embedded systems, mobile platforms, or cloud-native workloads.
Publications, conference presentations, or open-source contributions in security research or program analysis.
Prior experience in red team research or advanced threat modeling.